Overview

Dataset statistics

Number of variables29
Number of observations2358
Missing cells3
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory534.4 KiB
Average record size in memory232.1 B

Variable types

Text16
Unsupported4
Numeric4
Categorical5

Alerts

average_rating is highly overall correlated with country_codeHigh correlation
book_id is highly overall correlated with country_code and 4 other fieldsHigh correlation
ratings_count is highly overall correlated with text_reviews_count and 1 other fieldsHigh correlation
text_reviews_count is highly overall correlated with ratings_count and 1 other fieldsHigh correlation
country_code is highly overall correlated with average_rating and 4 other fieldsHigh correlation
format is highly overall correlated with book_id and 1 other fieldsHigh correlation
is_ebook is highly overall correlated with book_id and 2 other fieldsHigh correlation
publication_day is highly overall correlated with book_idHigh correlation
publication_month is highly overall correlated with book_idHigh correlation
country_code is highly imbalanced (99.5%)Imbalance
format is highly imbalanced (51.1%)Imbalance
ratings_count is highly skewed (γ1 = 27.15211267)Skewed
text_reviews_count is highly skewed (γ1 = 41.43024918)Skewed
book_id has unique valuesUnique
link has unique valuesUnique
url has unique valuesUnique
authors is an unsupported type, check if it needs cleaning or further analysisUnsupported
popular_shelves is an unsupported type, check if it needs cleaning or further analysisUnsupported
series is an unsupported type, check if it needs cleaning or further analysisUnsupported
similar_books is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-10-17 17:30:42.742821
Analysis finished2023-10-17 17:32:27.183941
Duration1 minute and 44.44 seconds
Software versionydata-profiling vv4.2.0
Download configurationconfig.json

Variables

asin
Text

Distinct472
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Memory size18.5 KiB
2023-10-17T19:32:27.387419image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length10
Median length0
Mean length1.9974555
Min length0

Characters and Unicode

Total characters4710
Distinct characters37
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique471 ?
Unique (%)20.0%

Sample

1st row
2nd row
3rd row
4th rowB00LRHW99U
5th row
ValueCountFrequency (%)
b005k0myx6 1
 
0.2%
b00uue5nvw 1
 
0.2%
b0051hhue6 1
 
0.2%
b01ku9rs9q 1
 
0.2%
b003v8bh6y 1
 
0.2%
asin:b00ec 1
 
0.2%
b002q0w8ne 1
 
0.2%
b003cju47u 1
 
0.2%
b00m6g8n6o 1
 
0.2%
b01gz77n9c 1
 
0.2%
Other values (461) 461
97.9%
2023-10-17T19:32:27.777321image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 865
 
18.4%
B 548
 
11.6%
1 225
 
4.8%
8 128
 
2.7%
6 126
 
2.7%
7 119
 
2.5%
G 114
 
2.4%
C 114
 
2.4%
M 113
 
2.4%
2 112
 
2.4%
Other values (27) 2246
47.7%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 2746
58.3%
Decimal Number 1963
41.7%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
B 548
20.0%
G 114
 
4.2%
C 114
 
4.2%
M 113
 
4.1%
J 104
 
3.8%
Y 103
 
3.8%
E 101
 
3.7%
O 100
 
3.6%
N 98
 
3.6%
K 98
 
3.6%
Other values (16) 1253
45.6%
Decimal Number
ValueCountFrequency (%)
0 865
44.1%
1 225
 
11.5%
8 128
 
6.5%
6 126
 
6.4%
7 119
 
6.1%
2 112
 
5.7%
4 111
 
5.7%
9 97
 
4.9%
5 94
 
4.8%
3 86
 
4.4%
Other Punctuation
ValueCountFrequency (%)
: 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2746
58.3%
Common 1964
41.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
B 548
20.0%
G 114
 
4.2%
C 114
 
4.2%
M 113
 
4.1%
J 104
 
3.8%
Y 103
 
3.8%
E 101
 
3.7%
O 100
 
3.6%
N 98
 
3.6%
K 98
 
3.6%
Other values (16) 1253
45.6%
Common
ValueCountFrequency (%)
0 865
44.0%
1 225
 
11.5%
8 128
 
6.5%
6 126
 
6.4%
7 119
 
6.1%
2 112
 
5.7%
4 111
 
5.7%
9 97
 
4.9%
5 94
 
4.8%
3 86
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4710
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 865
 
18.4%
B 548
 
11.6%
1 225
 
4.8%
8 128
 
2.7%
6 126
 
2.7%
7 119
 
2.5%
G 114
 
2.4%
C 114
 
2.4%
M 113
 
2.4%
2 112
 
2.4%
Other values (27) 2246
47.7%

authors
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size18.5 KiB

average_rating
Real number (ℝ)

Distinct212
Distinct (%)9.0%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean3.8923801
Minimum0
Maximum5
Zeros4
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size18.5 KiB
2023-10-17T19:32:27.954194image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3.03
Q13.66
median3.94
Q34.18
95-th percentile4.61
Maximum5
Range5
Interquartile range (IQR)0.52

Descriptive statistics

Standard deviation0.50786653
Coefficient of variation (CV)0.13047712
Kurtosis8.2051275
Mean3.8923801
Median Absolute Deviation (MAD)0.26
Skewness-1.4718413
Sum9174.34
Variance0.25792842
MonotonicityNot monotonic
2023-10-17T19:32:28.118709image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4 136
 
5.8%
5 66
 
2.8%
3.5 47
 
2.0%
3 46
 
2.0%
4.5 36
 
1.5%
4.1 35
 
1.5%
3.67 32
 
1.4%
4.33 32
 
1.4%
3.82 31
 
1.3%
4.25 30
 
1.3%
Other values (202) 1866
79.1%
ValueCountFrequency (%)
0 4
 
0.2%
1 4
 
0.2%
1.5 1
 
< 0.1%
1.83 1
 
< 0.1%
2 13
0.6%
2.25 1
 
< 0.1%
2.33 2
 
0.1%
2.44 1
 
< 0.1%
2.45 1
 
< 0.1%
2.47 1
 
< 0.1%
ValueCountFrequency (%)
5 66
2.8%
4.9 1
 
< 0.1%
4.86 3
 
0.1%
4.83 1
 
< 0.1%
4.82 2
 
0.1%
4.8 4
 
0.2%
4.79 1
 
< 0.1%
4.78 1
 
< 0.1%
4.77 1
 
< 0.1%
4.75 6
 
0.3%

book_id
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct2358
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15598475
Minimum1243
Maximum36389613
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size18.5 KiB
2023-10-17T19:32:28.287122image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1243
5-th percentile424220.1
Q16280683
median15891197
Q324306703
95-th percentile33795115
Maximum36389613
Range36388370
Interquartile range (IQR)18026020

Descriptive statistics

Standard deviation10776786
Coefficient of variation (CV)0.69088718
Kurtosis-1.1584471
Mean15598475
Median Absolute Deviation (MAD)9150353.5
Skewness0.13243909
Sum3.6781203 × 1010
Variance1.1613912 × 1014
MonotonicityNot monotonic
2023-10-17T19:32:28.450107image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
22554103 1
 
< 0.1%
22921692 1
 
< 0.1%
139055 1
 
< 0.1%
23656002 1
 
< 0.1%
19350065 1
 
< 0.1%
17343580 1
 
< 0.1%
32501293 1
 
< 0.1%
7160819 1
 
< 0.1%
13237352 1
 
< 0.1%
32182822 1
 
< 0.1%
Other values (2348) 2348
99.6%
ValueCountFrequency (%)
1243 1
< 0.1%
2881 1
< 0.1%
3615 1
< 0.1%
7136 1
< 0.1%
13509 1
< 0.1%
13719 1
< 0.1%
22416 1
< 0.1%
23824 1
< 0.1%
24059 1
< 0.1%
25445 1
< 0.1%
ValueCountFrequency (%)
36389613 1
< 0.1%
36388909 1
< 0.1%
36377848 1
< 0.1%
36347223 1
< 0.1%
36307310 1
< 0.1%
36301624 1
< 0.1%
36299813 1
< 0.1%
36287775 1
< 0.1%
36278975 1
< 0.1%
36273824 1
< 0.1%

country_code
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size18.5 KiB
US
2357 
 
1

Length

Max length2
Median length2
Mean length1.9991518
Min length0

Characters and Unicode

Total characters4714
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowUS
2nd rowUS
3rd rowUS
4th rowUS
5th rowUS

Common Values

ValueCountFrequency (%)
US 2357
> 99.9%
1
 
< 0.1%

Length

2023-10-17T19:32:28.615860image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-10-17T19:32:28.737104image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
us 2357
100.0%

Most occurring characters

ValueCountFrequency (%)
U 2357
50.0%
S 2357
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 4714
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
U 2357
50.0%
S 2357
50.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4714
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
U 2357
50.0%
S 2357
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4714
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
U 2357
50.0%
S 2357
50.0%
Distinct1940
Distinct (%)82.3%
Missing0
Missing (%)0.0%
Memory size18.5 KiB
2023-10-17T19:32:28.947712image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length5405
Median length1309
Mean length684.07167
Min length0

Characters and Unicode

Total characters1613041
Distinct characters95
Distinct categories13 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1937 ?
Unique (%)82.1%

Sample

1st rowAproximadamente en las mismas fechas en que escribia sus memorias esta prostituta vienesa, tambien redactaba las suyas, igualmente apasionantes, la gran cantante wagneriana Wilhelmine Shroeder-Devrient, autora de Memorias de una cantante alemana. Si esta fue una mujer refinada, culta y rica, aquella tuvo un origen humilde y fue precisamente gracias a la profesion mas antigua del mundo como adquirio modales y conocimientos suficientes como para poder redactar con acierto, ya al final de su vida, este extraordinario testimonio personal, escalofriante por su sinceridad, que entrego a su medico unas semanas antes de someterse a una grave operacion. Estas confesiones intimas de una prostituta no tienen tan solo el valor testimonial directo de una actividad en y por principio inconfesable, sino tambien el de ilustrar con todo lujo de detalles la vida amorosa de la sociedad vienesa de la segunda mitad del siglo XIX. Por eso sus primeros editores alemanes procuraron respetar al maximo el texto original.
2nd row
3rd rowThis is a workflow-based, time-saving handbook for the digital photography professional. Coverage is aimed squarely at the professional photographer who is making the switch from traditional to digital photography.
4th row"Tell the doctor where it hurts." It sounds simple enough, unless the problem affects the very organ that produces awareness and generates speech. What is it like to try to heal the body when the mind is under attack? In this book, Dr. Allan Ropper and Brian Burrell take the reader behind the scenes at Harvard Medical School's neurology unit to show how a seasoned diagnostician faces down bizarre, life-altering afflictions. Like Alice in Wonderland, Dr. Ropper inhabits a world where absurdities abound:* A figure skater whose body has become a ticking time-bomb * A salesman who drives around and around a traffic rotary, unable to get off * A college quarterback who can't stop calling the same play * A child molester who, after falling on the ice, is left with a brain that is very much dead inside a body that is very much alive * A mother of two young girls, diagnosed with ALS, who has to decide whether a life locked inside her own head is worth livingHow does one begin to treat such cases, to counsel people whose lives may be changed forever? How does one train the next generation of clinicians to deal with the moral and medical aspects of brain disease? Dr. Ropper and his colleague answer these questions by taking the reader into a rarified world where lives and minds hang in the balance.
5th row"Afrikaans hoort by Nederlands: ons Afrikaanse taalverdriet" is 'n boek (en verwerkte lisensiaatverhandeling) deur Petrus van Eeden. In hierdie boek betwis Van Eeden die funksionaliteit en bestaansreg van Afrikaans as die (na sy mening rypgedrukte) standaardtaal in Suid-Afrika. Hy pleit dat Afrikaners moet herbesin en Nederlands weer as kultuurtaal moet aanvaar. Van Eeden steun taalamalgamasie.
ValueCountFrequency (%)
the 12012
 
4.5%
and 7553
 
2.8%
a 7006
 
2.6%
of 6767
 
2.5%
to 6067
 
2.3%
in 3966
 
1.5%
is 2809
 
1.0%
her 2528
 
0.9%
his 2023
 
0.8%
for 1951
 
0.7%
Other values (45376) 215014
80.3%
2023-10-17T19:32:29.448853image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
261727
16.2%
e 153771
 
9.5%
a 109316
 
6.8%
t 100834
 
6.3%
i 94344
 
5.8%
n 93781
 
5.8%
o 92349
 
5.7%
s 84107
 
5.2%
r 81693
 
5.1%
h 60093
 
3.7%
Other values (85) 481026
29.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1246998
77.3%
Space Separator 261727
 
16.2%
Uppercase Letter 45399
 
2.8%
Other Punctuation 43310
 
2.7%
Dash Punctuation 5268
 
0.3%
Control 4101
 
0.3%
Decimal Number 4038
 
0.3%
Modifier Symbol 816
 
0.1%
Close Punctuation 465
 
< 0.1%
Open Punctuation 458
 
< 0.1%
Other values (3) 461
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 153771
12.3%
a 109316
 
8.8%
t 100834
 
8.1%
i 94344
 
7.6%
n 93781
 
7.5%
o 92349
 
7.4%
s 84107
 
6.7%
r 81693
 
6.6%
h 60093
 
4.8%
l 57205
 
4.6%
Other values (16) 319505
25.6%
Uppercase Letter
ValueCountFrequency (%)
T 4134
 
9.1%
A 3956
 
8.7%
S 3787
 
8.3%
B 2665
 
5.9%
I 2497
 
5.5%
C 2487
 
5.5%
H 2471
 
5.4%
M 2364
 
5.2%
D 2103
 
4.6%
W 2016
 
4.4%
Other values (16) 16919
37.3%
Other Punctuation
ValueCountFrequency (%)
, 16612
38.4%
. 15124
34.9%
' 5532
 
12.8%
" 2083
 
4.8%
? 1009
 
2.3%
: 857
 
2.0%
@ 581
 
1.3%
! 478
 
1.1%
; 366
 
0.8%
* 324
 
0.7%
Other values (4) 344
 
0.8%
Decimal Number
ValueCountFrequency (%)
1 911
22.6%
0 826
20.5%
2 482
11.9%
9 454
11.2%
8 279
 
6.9%
5 241
 
6.0%
3 238
 
5.9%
4 227
 
5.6%
7 197
 
4.9%
6 183
 
4.5%
Math Symbol
ValueCountFrequency (%)
~ 238
55.3%
> 81
 
18.8%
< 67
 
15.6%
+ 40
 
9.3%
= 4
 
0.9%
Close Punctuation
ValueCountFrequency (%)
) 439
94.4%
] 25
 
5.4%
} 1
 
0.2%
Open Punctuation
ValueCountFrequency (%)
( 433
94.5%
[ 24
 
5.2%
{ 1
 
0.2%
Control
ValueCountFrequency (%)
4071
99.3%
 30
 
0.7%
Modifier Symbol
ValueCountFrequency (%)
` 810
99.3%
^ 6
 
0.7%
Space Separator
ValueCountFrequency (%)
261727
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5268
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 23
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1292397
80.1%
Common 320644
 
19.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 153771
11.9%
a 109316
 
8.5%
t 100834
 
7.8%
i 94344
 
7.3%
n 93781
 
7.3%
o 92349
 
7.1%
s 84107
 
6.5%
r 81693
 
6.3%
h 60093
 
4.6%
l 57205
 
4.4%
Other values (42) 364904
28.2%
Common
ValueCountFrequency (%)
261727
81.6%
, 16612
 
5.2%
. 15124
 
4.7%
' 5532
 
1.7%
- 5268
 
1.6%
4071
 
1.3%
" 2083
 
0.6%
? 1009
 
0.3%
1 911
 
0.3%
: 857
 
0.3%
Other values (33) 7450
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1613041
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
261727
16.2%
e 153771
 
9.5%
a 109316
 
6.8%
t 100834
 
6.3%
i 94344
 
5.8%
n 93781
 
5.8%
o 92349
 
5.7%
s 84107
 
5.2%
r 81693
 
5.1%
h 60093
 
3.7%
Other values (85) 481026
29.8%
Distinct155
Distinct (%)6.6%
Missing0
Missing (%)0.0%
Memory size18.5 KiB
2023-10-17T19:32:29.720975image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length66
Median length0
Mean length1.3375742
Min length0

Characters and Unicode

Total characters3154
Distinct characters74
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique138 ?
Unique (%)5.9%

Sample

1st row
2nd row
3rd row
4th row
5th row
ValueCountFrequency (%)
edition 51
 
9.8%
1st 26
 
5.0%
first 26
 
5.0%
1 18
 
3.4%
print 14
 
2.7%
unabridged 12
 
2.3%
large 11
 
2.1%
harlequin 7
 
1.3%
2nd 7
 
1.3%
second 7
 
1.3%
Other values (263) 343
65.7%
2023-10-17T19:32:30.134171image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 312
 
9.9%
277
 
8.8%
e 257
 
8.1%
t 208
 
6.6%
r 188
 
6.0%
n 188
 
6.0%
o 162
 
5.1%
a 156
 
4.9%
s 153
 
4.9%
d 148
 
4.7%
Other values (64) 1105
35.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2313
73.3%
Uppercase Letter 343
 
10.9%
Space Separator 277
 
8.8%
Decimal Number 164
 
5.2%
Other Punctuation 35
 
1.1%
Dash Punctuation 12
 
0.4%
Math Symbol 5
 
0.2%
Modifier Symbol 3
 
0.1%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 312
13.5%
e 257
11.1%
t 208
9.0%
r 188
8.1%
n 188
8.1%
o 162
 
7.0%
a 156
 
6.7%
s 153
 
6.6%
d 148
 
6.4%
l 126
 
5.4%
Other values (16) 415
17.9%
Uppercase Letter
ValueCountFrequency (%)
E 40
11.7%
P 32
 
9.3%
F 32
 
9.3%
S 30
 
8.7%
L 27
 
7.9%
A 26
 
7.6%
U 19
 
5.5%
T 18
 
5.2%
B 17
 
5.0%
C 14
 
4.1%
Other values (14) 88
25.7%
Decimal Number
ValueCountFrequency (%)
1 64
39.0%
2 24
 
14.6%
0 17
 
10.4%
7 13
 
7.9%
5 11
 
6.7%
3 9
 
5.5%
4 8
 
4.9%
8 8
 
4.9%
9 7
 
4.3%
6 3
 
1.8%
Other Punctuation
ValueCountFrequency (%)
# 17
48.6%
. 5
 
14.3%
@ 4
 
11.4%
, 4
 
11.4%
' 3
 
8.6%
/ 1
 
2.9%
: 1
 
2.9%
Math Symbol
ValueCountFrequency (%)
~ 4
80.0%
+ 1
 
20.0%
Space Separator
ValueCountFrequency (%)
277
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2656
84.2%
Common 498
 
15.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 312
11.7%
e 257
 
9.7%
t 208
 
7.8%
r 188
 
7.1%
n 188
 
7.1%
o 162
 
6.1%
a 156
 
5.9%
s 153
 
5.8%
d 148
 
5.6%
l 126
 
4.7%
Other values (40) 758
28.5%
Common
ValueCountFrequency (%)
277
55.6%
1 64
 
12.9%
2 24
 
4.8%
0 17
 
3.4%
# 17
 
3.4%
7 13
 
2.6%
- 12
 
2.4%
5 11
 
2.2%
3 9
 
1.8%
4 8
 
1.6%
Other values (14) 46
 
9.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3154
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 312
 
9.9%
277
 
8.8%
e 257
 
8.1%
t 208
 
6.6%
r 188
 
6.0%
n 188
 
6.0%
o 162
 
5.1%
a 156
 
4.9%
s 153
 
4.9%
d 148
 
4.7%
Other values (64) 1105
35.0%

format
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct33
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size18.5 KiB
Paperback
871 
633 
Hardcover
358 
ebook
206 
Kindle Edition
135 
Other values (28)
155 

Length

Max length21
Median length9
Mean length6.8375742
Min length0

Characters and Unicode

Total characters16123
Distinct characters40
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)0.8%

Sample

1st rowHardcover
2nd rowHardcover
3rd rowPaperback
4th row
5th rowPaperback

Common Values

ValueCountFrequency (%)
Paperback 871
36.9%
633
26.8%
Hardcover 358
15.2%
ebook 206
 
8.7%
Kindle Edition 135
 
5.7%
Mass Market Paperback 57
 
2.4%
Audio CD 27
 
1.1%
Audiobook 18
 
0.8%
Audible Audio 12
 
0.5%
Audio 7
 
0.3%
Other values (23) 34
 
1.4%

Length

2023-10-17T19:32:30.302276image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
paperback 932
45.8%
hardcover 359
 
17.7%
ebook 206
 
10.1%
kindle 135
 
6.6%
edition 135
 
6.6%
mass 57
 
2.8%
market 57
 
2.8%
audio 48
 
2.4%
cd 27
 
1.3%
audiobook 18
 
0.9%
Other values (27) 59
 
2.9%

Most occurring characters

ValueCountFrequency (%)
a 2359
14.6%
r 1720
10.7%
e 1713
10.6%
c 1299
8.1%
k 1226
7.6%
b 1179
 
7.3%
o 1035
 
6.4%
p 940
 
5.8%
P 932
 
5.8%
d 724
 
4.5%
Other values (30) 2996
18.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 13961
86.6%
Uppercase Letter 1850
 
11.5%
Space Separator 308
 
1.9%
Dash Punctuation 3
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 2359
16.9%
r 1720
12.3%
e 1713
12.3%
c 1299
9.3%
k 1226
8.8%
b 1179
8.4%
o 1035
7.4%
p 940
 
6.7%
d 724
 
5.2%
i 508
 
3.6%
Other values (12) 1258
9.0%
Uppercase Letter
ValueCountFrequency (%)
P 932
50.4%
H 359
 
19.4%
K 135
 
7.3%
E 135
 
7.3%
M 118
 
6.4%
A 78
 
4.2%
C 33
 
1.8%
D 28
 
1.5%
B 15
 
0.8%
U 8
 
0.4%
Other values (5) 9
 
0.5%
Space Separator
ValueCountFrequency (%)
308
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 15811
98.1%
Common 312
 
1.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 2359
14.9%
r 1720
10.9%
e 1713
10.8%
c 1299
8.2%
k 1226
7.8%
b 1179
7.5%
o 1035
 
6.5%
p 940
 
5.9%
P 932
 
5.9%
d 724
 
4.6%
Other values (27) 2684
17.0%
Common
ValueCountFrequency (%)
308
98.7%
- 3
 
1.0%
+ 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16123
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 2359
14.6%
r 1720
10.7%
e 1713
10.6%
c 1299
8.1%
k 1226
7.6%
b 1179
 
7.3%
o 1035
 
6.4%
p 940
 
5.8%
P 932
 
5.8%
d 724
 
4.5%
Other values (30) 2996
18.6%
Distinct1406
Distinct (%)59.6%
Missing0
Missing (%)0.0%
Memory size18.5 KiB
2023-10-17T19:32:30.509509image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length88
Median length59
Mean length70.5
Min length0

Characters and Unicode

Total characters166239
Distinct characters33
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1405 ?
Unique (%)59.6%

Sample

1st rowhttps://images.gr-assets.com/books/1403253289m/22554103.jpg
2nd rowhttps://images.gr-assets.com/books/1345041681m/15829792.jpg
3rd rowhttps://s.gr-assets.com/assets/nophoto/book/111x148-bcc042a9c91a29c1d680899eff700a03.png
4th rowhttps://s.gr-assets.com/assets/nophoto/book/111x148-bcc042a9c91a29c1d680899eff700a03.png
5th rowhttps://s.gr-assets.com/assets/nophoto/book/111x148-bcc042a9c91a29c1d680899eff700a03.png
ValueCountFrequency (%)
https://s.gr-assets.com/assets/nophoto/book/111x148-bcc042a9c91a29c1d680899eff700a03.png 953
40.4%
https://images.gr-assets.com/books/1472006107m/30896674.jpg 1
 
< 0.1%
https://images.gr-assets.com/books/1291275163m/9368172.jpg 1
 
< 0.1%
https://images.gr-assets.com/books/1344705875m/13227511.jpg 1
 
< 0.1%
https://images.gr-assets.com/books/1328602085m/3379686.jpg 1
 
< 0.1%
https://images.gr-assets.com/books/1373999220m/18206694.jpg 1
 
< 0.1%
https://images.gr-assets.com/books/1420756607m/23273757.jpg 1
 
< 0.1%
https://images.gr-assets.com/books/1452429925m/28502768.jpg 1
 
< 0.1%
https://images.gr-assets.com/books/1361050496m/17378852.jpg 1
 
< 0.1%
https://images.gr-assets.com/books/1328248849m/9835758.jpg 1
 
< 0.1%
Other values (1395) 1395
59.2%
2023-10-17T19:32:30.916147image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 16048
 
9.7%
/ 12738
 
7.7%
o 9930
 
6.0%
1 9686
 
5.8%
t 8977
 
5.4%
a 7573
 
4.6%
. 7071
 
4.3%
0 6842
 
4.1%
9 6759
 
4.1%
c 6169
 
3.7%
Other values (23) 74446
44.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 91174
54.8%
Decimal Number 49589
29.8%
Other Punctuation 22166
 
13.3%
Dash Punctuation 3310
 
2.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s 16048
17.6%
o 9930
10.9%
t 8977
9.8%
a 7573
8.3%
c 6169
 
6.8%
g 6118
 
6.7%
p 5667
 
6.2%
e 5667
 
6.2%
m 5165
 
5.7%
h 3310
 
3.6%
Other values (9) 16550
18.2%
Decimal Number
ValueCountFrequency (%)
1 9686
19.5%
0 6842
13.8%
9 6759
13.6%
8 5038
10.2%
4 4598
9.3%
2 4433
8.9%
3 3969
8.0%
7 3156
 
6.4%
6 3013
 
6.1%
5 2095
 
4.2%
Other Punctuation
ValueCountFrequency (%)
/ 12738
57.5%
. 7071
31.9%
: 2357
 
10.6%
Dash Punctuation
ValueCountFrequency (%)
- 3310
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 91174
54.8%
Common 75065
45.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
s 16048
17.6%
o 9930
10.9%
t 8977
9.8%
a 7573
8.3%
c 6169
 
6.8%
g 6118
 
6.7%
p 5667
 
6.2%
e 5667
 
6.2%
m 5165
 
5.7%
h 3310
 
3.6%
Other values (9) 16550
18.2%
Common
ValueCountFrequency (%)
/ 12738
17.0%
1 9686
12.9%
. 7071
9.4%
0 6842
9.1%
9 6759
9.0%
8 5038
 
6.7%
4 4598
 
6.1%
2 4433
 
5.9%
3 3969
 
5.3%
- 3310
 
4.4%
Other values (4) 10621
14.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 166239
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
s 16048
 
9.7%
/ 12738
 
7.7%
o 9930
 
6.0%
1 9686
 
5.8%
t 8977
 
5.4%
a 7573
 
4.6%
. 7071
 
4.3%
0 6842
 
4.1%
9 6759
 
4.1%
c 6169
 
3.7%
Other values (23) 74446
44.8%

is_ebook
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size18.5 KiB
false
1662 
true
695 
 
1

Length

Max length5
Median length5
Mean length4.7031383
Min length0

Characters and Unicode

Total characters11090
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowfalse
2nd rowfalse
3rd rowfalse
4th rowtrue
5th rowfalse

Common Values

ValueCountFrequency (%)
false 1662
70.5%
true 695
29.5%
1
 
< 0.1%

Length

2023-10-17T19:32:31.085978image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-10-17T19:32:31.242201image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
false 1662
70.5%
true 695
29.5%

Most occurring characters

ValueCountFrequency (%)
e 2357
21.3%
f 1662
15.0%
a 1662
15.0%
l 1662
15.0%
s 1662
15.0%
t 695
 
6.3%
r 695
 
6.3%
u 695
 
6.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 11090
100.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 2357
21.3%
f 1662
15.0%
a 1662
15.0%
l 1662
15.0%
s 1662
15.0%
t 695
 
6.3%
r 695
 
6.3%
u 695
 
6.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 11090
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 2357
21.3%
f 1662
15.0%
a 1662
15.0%
l 1662
15.0%
s 1662
15.0%
t 695
 
6.3%
r 695
 
6.3%
u 695
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11090
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 2357
21.3%
f 1662
15.0%
a 1662
15.0%
l 1662
15.0%
s 1662
15.0%
t 695
 
6.3%
r 695
 
6.3%
u 695
 
6.3%

isbn
Text

Distinct1343
Distinct (%)57.0%
Missing0
Missing (%)0.0%
Memory size18.5 KiB
2023-10-17T19:32:31.490220image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length10
Median length10
Mean length5.6904156
Min length0

Characters and Unicode

Total characters13418
Distinct characters20
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1342 ?
Unique (%)56.9%

Sample

1st row8422669552
2nd row8496722125
3rd row0735712360
4th row
5th row1874976139
ValueCountFrequency (%)
8422669552 1
 
0.1%
0989812812 1
 
0.1%
1874976139 1
 
0.1%
0982658710 1
 
0.1%
1613740557 1
 
0.1%
0006386849 1
 
0.1%
0786474807 1
 
0.1%
8496390993 1
 
0.1%
0061757179 1
 
0.1%
085768647x 1
 
0.1%
Other values (1332) 1332
99.3%
2023-10-17T19:32:31.970269image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1936
14.4%
1 1682
12.5%
4 1349
10.1%
5 1256
9.4%
8 1229
9.2%
3 1201
9.0%
9 1186
8.8%
7 1184
8.8%
2 1155
8.6%
6 1108
8.3%
Other values (10) 132
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 13286
99.0%
Uppercase Letter 131
 
1.0%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1936
14.6%
1 1682
12.7%
4 1349
10.2%
5 1256
9.5%
8 1229
9.3%
3 1201
9.0%
9 1186
8.9%
7 1184
8.9%
2 1155
8.7%
6 1108
8.3%
Uppercase Letter
ValueCountFrequency (%)
X 123
93.9%
N 1
 
0.8%
A 1
 
0.8%
F 1
 
0.8%
B 1
 
0.8%
I 1
 
0.8%
R 1
 
0.8%
S 1
 
0.8%
Y 1
 
0.8%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 13287
99.0%
Latin 131
 
1.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1936
14.6%
1 1682
12.7%
4 1349
10.2%
5 1256
9.5%
8 1229
9.2%
3 1201
9.0%
9 1186
8.9%
7 1184
8.9%
2 1155
8.7%
6 1108
8.3%
Latin
ValueCountFrequency (%)
X 123
93.9%
N 1
 
0.8%
A 1
 
0.8%
F 1
 
0.8%
B 1
 
0.8%
I 1
 
0.8%
R 1
 
0.8%
S 1
 
0.8%
Y 1
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13418
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1936
14.4%
1 1682
12.5%
4 1349
10.1%
5 1256
9.4%
8 1229
9.2%
3 1201
9.0%
9 1186
8.8%
7 1184
8.8%
2 1155
8.6%
6 1108
8.3%
Other values (10) 132
 
1.0%

isbn13
Text

Distinct1556
Distinct (%)66.0%
Missing0
Missing (%)0.0%
Memory size18.5 KiB
2023-10-17T19:32:32.186361image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length13
Median length13
Mean length8.56743
Min length0

Characters and Unicode

Total characters20202
Distinct characters25
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1555 ?
Unique (%)65.9%

Sample

1st row
2nd row9788496722125
3rd row9780735712362
4th row
5th row
ValueCountFrequency (%)
9781944449278 1
 
0.1%
9789029079655 1
 
0.1%
9780735712362 1
 
0.1%
9780982658710 1
 
0.1%
9781613740552 1
 
0.1%
9780006386841 1
 
0.1%
9780786474806 1
 
0.1%
9781310401053 1
 
0.1%
9788430534937 1
 
0.1%
9780061757174 1
 
0.1%
Other values (1545) 1545
99.4%
2023-10-17T19:32:32.569991image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9 2984
14.8%
8 2933
14.5%
7 2917
14.4%
0 2220
11.0%
1 1981
9.8%
4 1547
7.7%
5 1451
7.2%
3 1406
7.0%
2 1385
6.9%
6 1355
6.7%
Other values (15) 23
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 20179
99.9%
Uppercase Letter 22
 
0.1%
Open Punctuation 1
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
B 4
18.2%
U 3
13.6%
G 2
9.1%
N 2
9.1%
D 2
9.1%
T 1
 
4.5%
I 1
 
4.5%
Q 1
 
4.5%
C 1
 
4.5%
Z 1
 
4.5%
Other values (4) 4
18.2%
Decimal Number
ValueCountFrequency (%)
9 2984
14.8%
8 2933
14.5%
7 2917
14.5%
0 2220
11.0%
1 1981
9.8%
4 1547
7.7%
5 1451
7.2%
3 1406
7.0%
2 1385
6.9%
6 1355
6.7%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 20180
99.9%
Latin 22
 
0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
B 4
18.2%
U 3
13.6%
G 2
9.1%
N 2
9.1%
D 2
9.1%
T 1
 
4.5%
I 1
 
4.5%
Q 1
 
4.5%
C 1
 
4.5%
Z 1
 
4.5%
Other values (4) 4
18.2%
Common
ValueCountFrequency (%)
9 2984
14.8%
8 2933
14.5%
7 2917
14.5%
0 2220
11.0%
1 1981
9.8%
4 1547
7.7%
5 1451
7.2%
3 1406
7.0%
2 1385
6.9%
6 1355
6.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 20202
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9 2984
14.8%
8 2933
14.5%
7 2917
14.4%
0 2220
11.0%
1 1981
9.8%
4 1547
7.7%
5 1451
7.2%
3 1406
7.0%
2 1385
6.9%
6 1355
6.7%
Other values (15) 23
 
0.1%
Distinct998
Distinct (%)42.3%
Missing0
Missing (%)0.0%
Memory size18.5 KiB
2023-10-17T19:32:32.859612image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length10
Median length0
Mean length4.2366412
Min length0

Characters and Unicode

Total characters9990
Distinct characters36
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique995 ?
Unique (%)42.2%

Sample

1st row
2nd row
3rd rowB006OJ42PU
4th row
5th row
ValueCountFrequency (%)
b00j8gnuko 2
 
0.2%
b0189ehc54 2
 
0.2%
b005xmkduc 1
 
0.1%
b003cju47u 1
 
0.1%
b00h9j9ztm 1
 
0.1%
b0084am2h2 1
 
0.1%
b008g36k5c 1
 
0.1%
b008b945e4 1
 
0.1%
b00gdic3nk 1
 
0.1%
b01ku9rs9q 1
 
0.1%
Other values (987) 987
98.8%
2023-10-17T19:32:33.318679image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1984
19.9%
B 1168
 
11.7%
1 379
 
3.8%
6 274
 
2.7%
C 263
 
2.6%
4 257
 
2.6%
8 242
 
2.4%
G 238
 
2.4%
2 235
 
2.4%
7 223
 
2.2%
Other values (26) 4727
47.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 5811
58.2%
Decimal Number 4179
41.8%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
B 1168
20.1%
C 263
 
4.5%
G 238
 
4.1%
E 220
 
3.8%
A 216
 
3.7%
O 214
 
3.7%
U 213
 
3.7%
K 212
 
3.6%
I 210
 
3.6%
M 203
 
3.5%
Other values (16) 2654
45.7%
Decimal Number
ValueCountFrequency (%)
0 1984
47.5%
1 379
 
9.1%
6 274
 
6.6%
4 257
 
6.1%
8 242
 
5.8%
2 235
 
5.6%
7 223
 
5.3%
3 205
 
4.9%
5 196
 
4.7%
9 184
 
4.4%

Most occurring scripts

ValueCountFrequency (%)
Latin 5811
58.2%
Common 4179
41.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
B 1168
20.1%
C 263
 
4.5%
G 238
 
4.1%
E 220
 
3.8%
A 216
 
3.7%
O 214
 
3.7%
U 213
 
3.7%
K 212
 
3.6%
I 210
 
3.6%
M 203
 
3.5%
Other values (16) 2654
45.7%
Common
ValueCountFrequency (%)
0 1984
47.5%
1 379
 
9.1%
6 274
 
6.6%
4 257
 
6.1%
8 242
 
5.8%
2 235
 
5.6%
7 223
 
5.3%
3 205
 
4.9%
5 196
 
4.7%
9 184
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9990
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1984
19.9%
B 1168
 
11.7%
1 379
 
3.8%
6 274
 
2.7%
C 263
 
2.6%
4 257
 
2.6%
8 242
 
2.4%
G 238
 
2.4%
2 235
 
2.4%
7 223
 
2.2%
Other values (26) 4727
47.3%
Distinct51
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size18.5 KiB
2023-10-17T19:32:33.526878image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length5
Median length3
Mean length1.8210348
Min length0

Characters and Unicode

Total characters4294
Distinct characters30
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)0.6%

Sample

1st rowspa
2nd rowspa
3rd row
4th row
5th rowafr
ValueCountFrequency (%)
eng 720
54.1%
en-us 95
 
7.1%
ita 66
 
5.0%
spa 59
 
4.4%
en-gb 52
 
3.9%
ara 42
 
3.2%
fre 41
 
3.1%
ind 27
 
2.0%
ger 23
 
1.7%
por 23
 
1.7%
Other values (40) 184
 
13.8%
2023-10-17T19:32:33.880494image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 992
23.1%
n 957
22.3%
g 756
17.6%
a 231
 
5.4%
r 191
 
4.4%
- 156
 
3.6%
i 120
 
2.8%
p 106
 
2.5%
U 95
 
2.2%
S 95
 
2.2%
Other values (20) 595
13.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3826
89.1%
Uppercase Letter 312
 
7.3%
Dash Punctuation 156
 
3.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 992
25.9%
n 957
25.0%
g 756
19.8%
a 231
 
6.0%
r 191
 
5.0%
i 120
 
3.1%
p 106
 
2.8%
t 93
 
2.4%
s 86
 
2.2%
f 58
 
1.5%
Other values (13) 236
 
6.2%
Uppercase Letter
ValueCountFrequency (%)
U 95
30.4%
S 95
30.4%
G 52
16.7%
B 52
16.7%
C 9
 
2.9%
A 9
 
2.9%
Dash Punctuation
ValueCountFrequency (%)
- 156
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4138
96.4%
Common 156
 
3.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 992
24.0%
n 957
23.1%
g 756
18.3%
a 231
 
5.6%
r 191
 
4.6%
i 120
 
2.9%
p 106
 
2.6%
U 95
 
2.3%
S 95
 
2.3%
t 93
 
2.2%
Other values (19) 502
12.1%
Common
ValueCountFrequency (%)
- 156
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4294
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 992
23.1%
n 957
22.3%
g 756
17.6%
a 231
 
5.4%
r 191
 
4.4%
- 156
 
3.6%
i 120
 
2.8%
p 106
 
2.5%
U 95
 
2.2%
S 95
 
2.2%
Other values (20) 595
13.9%

link
Text

Distinct2358
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size18.5 KiB
2023-10-17T19:32:34.181515image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length133
Median length109
Mean length63.085242
Min length0

Characters and Unicode

Total characters148755
Distinct characters66
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2358 ?
Unique (%)100.0%

Sample

1st rowhttps://www.goodreads.com/book/show/22554103-historia-de-una-prostituta-vienesa
2nd rowhttps://www.goodreads.com/book/show/15829792-3-segundos
3rd rowhttps://www.goodreads.com/book/show/92838.The_Photoshop_Book_for_Digital_Photographers
4th rowhttps://www.goodreads.com/book/show/23460726-reaching-down-the-rabbit-hole
5th rowhttps://www.goodreads.com/book/show/27983357-afrikaans-hoort-by-nederlands
ValueCountFrequency (%)
https://www.goodreads.com/book/show/22554103-historia-de-una-prostituta-vienesa 1
 
< 0.1%
https://www.goodreads.com/book/show/30634831-devlin-s-daughter 1
 
< 0.1%
https://www.goodreads.com/book/show/18206694-women-and-fitness-in-american-culture 1
 
< 0.1%
https://www.goodreads.com/book/show/92838.the_photoshop_book_for_digital_photographers 1
 
< 0.1%
https://www.goodreads.com/book/show/23460726-reaching-down-the-rabbit-hole 1
 
< 0.1%
https://www.goodreads.com/book/show/27983357-afrikaans-hoort-by-nederlands 1
 
< 0.1%
https://www.goodreads.com/book/show/9368172-the-mystery-of-the-hidden-driveway 1
 
< 0.1%
https://www.goodreads.com/book/show/13227511-the-man-with-the-bionic-brain 1
 
< 0.1%
https://www.goodreads.com/book/show/3379686-vivienne-westwood 1
 
< 0.1%
https://www.goodreads.com/book/show/23273757-tainted 1
 
< 0.1%
Other values (2347) 2347
99.6%
2023-10-17T19:32:34.731011image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 16992
 
11.4%
/ 11785
 
7.9%
w 9887
 
6.6%
s 9424
 
6.3%
t 7430
 
5.0%
e 6833
 
4.6%
- 6542
 
4.4%
h 6387
 
4.3%
d 6125
 
4.1%
a 5477
 
3.7%
Other values (56) 61873
41.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 102480
68.9%
Other Punctuation 19289
 
13.0%
Decimal Number 17983
 
12.1%
Dash Punctuation 6542
 
4.4%
Uppercase Letter 1275
 
0.9%
Connector Punctuation 1186
 
0.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 16992
16.6%
w 9887
 
9.6%
s 9424
 
9.2%
t 7430
 
7.3%
e 6833
 
6.7%
h 6387
 
6.2%
d 6125
 
6.0%
a 5477
 
5.3%
r 4952
 
4.8%
c 3378
 
3.3%
Other values (16) 25595
25.0%
Uppercase Letter
ValueCountFrequency (%)
T 162
 
12.7%
S 127
 
10.0%
C 90
 
7.1%
W 78
 
6.1%
A 77
 
6.0%
B 77
 
6.0%
M 72
 
5.6%
L 61
 
4.8%
H 60
 
4.7%
G 54
 
4.2%
Other values (15) 417
32.7%
Decimal Number
ValueCountFrequency (%)
1 2456
13.7%
2 2315
12.9%
3 1999
11.1%
7 1720
9.6%
6 1621
9.0%
8 1611
9.0%
5 1610
9.0%
0 1574
8.8%
4 1559
8.7%
9 1518
8.4%
Other Punctuation
ValueCountFrequency (%)
/ 11785
61.1%
. 5147
26.7%
: 2357
 
12.2%
Dash Punctuation
ValueCountFrequency (%)
- 6542
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1186
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 103755
69.7%
Common 45000
30.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 16992
16.4%
w 9887
 
9.5%
s 9424
 
9.1%
t 7430
 
7.2%
e 6833
 
6.6%
h 6387
 
6.2%
d 6125
 
5.9%
a 5477
 
5.3%
r 4952
 
4.8%
c 3378
 
3.3%
Other values (41) 26870
25.9%
Common
ValueCountFrequency (%)
/ 11785
26.2%
- 6542
14.5%
. 5147
11.4%
1 2456
 
5.5%
: 2357
 
5.2%
2 2315
 
5.1%
3 1999
 
4.4%
7 1720
 
3.8%
6 1621
 
3.6%
8 1611
 
3.6%
Other values (5) 7447
16.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 148755
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 16992
 
11.4%
/ 11785
 
7.9%
w 9887
 
6.6%
s 9424
 
6.3%
t 7430
 
5.0%
e 6833
 
4.6%
- 6542
 
4.4%
h 6387
 
4.3%
d 6125
 
4.1%
a 5477
 
3.7%
Other values (56) 61873
41.6%
Distinct474
Distinct (%)20.1%
Missing0
Missing (%)0.0%
Memory size18.5 KiB
2023-10-17T19:32:35.078915image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length4
Median length3
Mean length1.9003393
Min length0

Characters and Unicode

Total characters4481
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique198 ?
Unique (%)8.4%

Sample

1st row270
2nd row72
3rd row358
4th row
5th row232
ValueCountFrequency (%)
304 38
 
2.4%
256 38
 
2.4%
32 36
 
2.3%
288 30
 
1.9%
320 29
 
1.8%
160 28
 
1.8%
192 27
 
1.7%
240 24
 
1.5%
272 23
 
1.4%
336 23
 
1.4%
Other values (463) 1292
81.4%
2023-10-17T19:32:35.620566image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 870
19.4%
1 566
12.6%
3 562
12.5%
4 549
12.3%
0 470
10.5%
8 413
9.2%
6 361
8.1%
5 272
 
6.1%
7 236
 
5.3%
9 182
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4481
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 870
19.4%
1 566
12.6%
3 562
12.5%
4 549
12.3%
0 470
10.5%
8 413
9.2%
6 361
8.1%
5 272
 
6.1%
7 236
 
5.3%
9 182
 
4.1%

Most occurring scripts

ValueCountFrequency (%)
Common 4481
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 870
19.4%
1 566
12.6%
3 562
12.5%
4 549
12.3%
0 470
10.5%
8 413
9.2%
6 361
8.1%
5 272
 
6.1%
7 236
 
5.3%
9 182
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4481
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 870
19.4%
1 566
12.6%
3 562
12.5%
4 549
12.3%
0 470
10.5%
8 413
9.2%
6 361
8.1%
5 272
 
6.1%
7 236
 
5.3%
9 182
 
4.1%

popular_shelves
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size18.5 KiB

publication_day
Categorical

Distinct32
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size18.5 KiB
1051 
1
338 
15
 
51
5
 
49
30
 
42
Other values (27)
827 

Length

Max length2
Median length1
Mean length0.84563189
Min length0

Characters and Unicode

Total characters1994
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row
3rd row5
4th row
5th row

Common Values

ValueCountFrequency (%)
1051
44.6%
1 338
 
14.3%
15 51
 
2.2%
5 49
 
2.1%
30 42
 
1.8%
2 42
 
1.8%
7 41
 
1.7%
20 40
 
1.7%
6 39
 
1.7%
28 37
 
1.6%
Other values (22) 628
26.6%

Length

2023-10-17T19:32:35.781602image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
1 338
25.9%
15 51
 
3.9%
5 49
 
3.7%
30 42
 
3.2%
2 42
 
3.2%
7 41
 
3.1%
20 40
 
3.1%
6 39
 
3.0%
28 37
 
2.8%
4 36
 
2.8%
Other values (21) 592
45.3%

Most occurring characters

ValueCountFrequency (%)
1 733
36.8%
2 407
20.4%
3 152
 
7.6%
5 133
 
6.7%
0 113
 
5.7%
7 103
 
5.2%
6 99
 
5.0%
4 93
 
4.7%
8 85
 
4.3%
9 76
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1994
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 733
36.8%
2 407
20.4%
3 152
 
7.6%
5 133
 
6.7%
0 113
 
5.7%
7 103
 
5.2%
6 99
 
5.0%
4 93
 
4.7%
8 85
 
4.3%
9 76
 
3.8%

Most occurring scripts

ValueCountFrequency (%)
Common 1994
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 733
36.8%
2 407
20.4%
3 152
 
7.6%
5 133
 
6.7%
0 113
 
5.7%
7 103
 
5.2%
6 99
 
5.0%
4 93
 
4.7%
8 85
 
4.3%
9 76
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1994
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 733
36.8%
2 407
20.4%
3 152
 
7.6%
5 133
 
6.7%
0 113
 
5.7%
7 103
 
5.2%
6 99
 
5.0%
4 93
 
4.7%
8 85
 
4.3%
9 76
 
3.8%
Distinct13
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size18.5 KiB
911 
10
146 
1
144 
9
141 
3
137 
Other values (8)
879 

Length

Max length2
Median length1
Mean length0.76505513
Min length0

Characters and Unicode

Total characters1804
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row3
3rd row3
4th row
5th row7

Common Values

ValueCountFrequency (%)
911
38.6%
10 146
 
6.2%
1 144
 
6.1%
9 141
 
6.0%
3 137
 
5.8%
5 121
 
5.1%
11 119
 
5.0%
4 118
 
5.0%
8 112
 
4.7%
2 107
 
4.5%
Other values (3) 302
 
12.8%

Length

2023-10-17T19:32:35.919932image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
10 146
10.1%
1 144
10.0%
9 141
9.7%
3 137
9.5%
5 121
8.4%
11 119
8.2%
4 118
8.2%
8 112
7.7%
2 107
7.4%
7 105
7.3%
Other values (2) 197
13.6%

Most occurring characters

ValueCountFrequency (%)
1 620
34.4%
2 199
 
11.0%
0 146
 
8.1%
9 141
 
7.8%
3 137
 
7.6%
5 121
 
6.7%
4 118
 
6.5%
8 112
 
6.2%
7 105
 
5.8%
6 105
 
5.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1804
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 620
34.4%
2 199
 
11.0%
0 146
 
8.1%
9 141
 
7.8%
3 137
 
7.6%
5 121
 
6.7%
4 118
 
6.5%
8 112
 
6.2%
7 105
 
5.8%
6 105
 
5.8%

Most occurring scripts

ValueCountFrequency (%)
Common 1804
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 620
34.4%
2 199
 
11.0%
0 146
 
8.1%
9 141
 
7.8%
3 137
 
7.6%
5 121
 
6.7%
4 118
 
6.5%
8 112
 
6.2%
7 105
 
5.8%
6 105
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1804
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 620
34.4%
2 199
 
11.0%
0 146
 
8.1%
9 141
 
7.8%
3 137
 
7.6%
5 121
 
6.7%
4 118
 
6.5%
8 112
 
6.2%
7 105
 
5.8%
6 105
 
5.8%
Distinct77
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size18.5 KiB
2023-10-17T19:32:36.052381image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length4
Median length4
Mean length2.9800679
Min length0

Characters and Unicode

Total characters7027
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)0.7%

Sample

1st row1998
2nd row2012
3rd row2003
4th row
5th row1995
ValueCountFrequency (%)
2013 173
 
9.8%
2014 153
 
8.7%
2012 147
 
8.4%
2015 141
 
8.0%
2016 127
 
7.2%
2011 104
 
5.9%
2010 102
 
5.8%
2007 80
 
4.6%
2009 74
 
4.2%
2008 68
 
3.9%
Other values (66) 588
33.5%
2023-10-17T19:32:36.314595image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2064
29.4%
2 1659
23.6%
1 1444
20.5%
9 555
 
7.9%
3 243
 
3.5%
4 226
 
3.2%
5 223
 
3.2%
6 222
 
3.2%
7 212
 
3.0%
8 179
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7027
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2064
29.4%
2 1659
23.6%
1 1444
20.5%
9 555
 
7.9%
3 243
 
3.5%
4 226
 
3.2%
5 223
 
3.2%
6 222
 
3.2%
7 212
 
3.0%
8 179
 
2.5%

Most occurring scripts

ValueCountFrequency (%)
Common 7027
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2064
29.4%
2 1659
23.6%
1 1444
20.5%
9 555
 
7.9%
3 243
 
3.5%
4 226
 
3.2%
5 223
 
3.2%
6 222
 
3.2%
7 212
 
3.0%
8 179
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7027
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2064
29.4%
2 1659
23.6%
1 1444
20.5%
9 555
 
7.9%
3 243
 
3.5%
4 226
 
3.2%
5 223
 
3.2%
6 222
 
3.2%
7 212
 
3.0%
8 179
 
2.5%
Distinct1291
Distinct (%)54.7%
Missing0
Missing (%)0.0%
Memory size18.5 KiB
2023-10-17T19:32:36.536078image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length91
Median length48
Mean length11.452502
Min length0

Characters and Unicode

Total characters27005
Distinct characters77
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1086 ?
Unique (%)46.1%

Sample

1st rowCirculo de lectores
2nd rowEdiciones Sinsentido
3rd rowNew Riders Publishing
4th row
5th rowBrevitas
ValueCountFrequency (%)
books 194
 
5.0%
press 189
 
4.8%
publishing 148
 
3.8%
67
 
1.7%
university 47
 
1.2%
createspace 42
 
1.1%
publishers 37
 
0.9%
house 33
 
0.8%
media 32
 
0.8%
penguin 25
 
0.6%
Other values (1676) 3096
79.2%
2023-10-17T19:32:37.057482image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2223
 
8.2%
e 2069
 
7.7%
i 1829
 
6.8%
o 1769
 
6.6%
s 1767
 
6.5%
a 1699
 
6.3%
r 1678
 
6.2%
n 1573
 
5.8%
l 1134
 
4.2%
t 1028
 
3.8%
Other values (67) 10236
37.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 20251
75.0%
Uppercase Letter 4073
 
15.1%
Space Separator 2223
 
8.2%
Other Punctuation 322
 
1.2%
Dash Punctuation 30
 
0.1%
Open Punctuation 29
 
0.1%
Close Punctuation 29
 
0.1%
Modifier Symbol 23
 
0.1%
Decimal Number 22
 
0.1%
Math Symbol 3
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 2069
10.2%
i 1829
 
9.0%
o 1769
 
8.7%
s 1767
 
8.7%
a 1699
 
8.4%
r 1678
 
8.3%
n 1573
 
7.8%
l 1134
 
5.6%
t 1028
 
5.1%
u 773
 
3.8%
Other values (16) 4932
24.4%
Uppercase Letter
ValueCountFrequency (%)
P 642
15.8%
B 392
 
9.6%
C 342
 
8.4%
S 312
 
7.7%
A 240
 
5.9%
H 221
 
5.4%
M 216
 
5.3%
L 204
 
5.0%
T 174
 
4.3%
E 157
 
3.9%
Other values (16) 1173
28.8%
Other Punctuation
ValueCountFrequency (%)
. 96
29.8%
& 59
18.3%
' 55
17.1%
, 55
17.1%
@ 37
 
11.5%
/ 12
 
3.7%
! 3
 
0.9%
: 2
 
0.6%
" 2
 
0.6%
; 1
 
0.3%
Decimal Number
ValueCountFrequency (%)
3 6
27.3%
1 5
22.7%
2 3
13.6%
4 2
 
9.1%
5 2
 
9.1%
8 1
 
4.5%
0 1
 
4.5%
7 1
 
4.5%
9 1
 
4.5%
Space Separator
ValueCountFrequency (%)
2223
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 30
100.0%
Open Punctuation
ValueCountFrequency (%)
( 29
100.0%
Close Punctuation
ValueCountFrequency (%)
) 29
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 23
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 24324
90.1%
Common 2681
 
9.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 2069
 
8.5%
i 1829
 
7.5%
o 1769
 
7.3%
s 1767
 
7.3%
a 1699
 
7.0%
r 1678
 
6.9%
n 1573
 
6.5%
l 1134
 
4.7%
t 1028
 
4.2%
u 773
 
3.2%
Other values (42) 9005
37.0%
Common
ValueCountFrequency (%)
2223
82.9%
. 96
 
3.6%
& 59
 
2.2%
' 55
 
2.1%
, 55
 
2.1%
@ 37
 
1.4%
- 30
 
1.1%
( 29
 
1.1%
) 29
 
1.1%
` 23
 
0.9%
Other values (15) 45
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 27005
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2223
 
8.2%
e 2069
 
7.7%
i 1829
 
6.8%
o 1769
 
6.6%
s 1767
 
6.5%
a 1699
 
6.3%
r 1678
 
6.2%
n 1573
 
5.8%
l 1134
 
4.2%
t 1028
 
3.8%
Other values (67) 10236
37.9%

ratings_count
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct438
Distinct (%)18.6%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean263.39627
Minimum0
Maximum85877
Zeros10
Zeros (%)0.4%
Negative0
Negative (%)0.0%
Memory size18.5 KiB
2023-10-17T19:32:37.275707image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q15
median20
Q375
95-th percentile616
Maximum85877
Range85877
Interquartile range (IQR)70

Descriptive statistics

Standard deviation2254.4357
Coefficient of variation (CV)8.5591027
Kurtosis932.72404
Mean263.39627
Median Absolute Deviation (MAD)17
Skewness27.152113
Sum620825
Variance5082480.3
MonotonicityNot monotonic
2023-10-17T19:32:37.467038image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 169
 
7.2%
2 129
 
5.5%
3 113
 
4.8%
4 99
 
4.2%
5 72
 
3.1%
6 64
 
2.7%
7 62
 
2.6%
11 56
 
2.4%
8 55
 
2.3%
10 48
 
2.0%
Other values (428) 1490
63.2%
ValueCountFrequency (%)
0 10
 
0.4%
1 169
7.2%
2 129
5.5%
3 113
4.8%
4 99
4.2%
5 72
3.1%
6 64
 
2.7%
7 62
 
2.6%
8 55
 
2.3%
9 46
 
2.0%
ValueCountFrequency (%)
85877 1
< 0.1%
36463 1
< 0.1%
31103 1
< 0.1%
23588 1
< 0.1%
13442 1
< 0.1%
13350 1
< 0.1%
12811 1
< 0.1%
11426 1
< 0.1%
11037 1
< 0.1%
10432 1
< 0.1%

series
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size18.5 KiB

similar_books
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size18.5 KiB

text_reviews_count
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct150
Distinct (%)6.4%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean22.820535
Minimum1
Maximum10183
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size18.5 KiB
2023-10-17T19:32:37.665355image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q311
95-th percentile60.2
Maximum10183
Range10182
Interquartile range (IQR)9

Descriptive statistics

Standard deviation221.35439
Coefficient of variation (CV)9.6997898
Kurtosis1887.3606
Mean22.820535
Median Absolute Deviation (MAD)3
Skewness41.430249
Sum53788
Variance48997.765
MonotonicityNot monotonic
2023-10-17T19:32:37.865215image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 582
24.7%
2 337
14.3%
3 210
 
8.9%
4 160
 
6.8%
5 132
 
5.6%
6 95
 
4.0%
7 90
 
3.8%
8 77
 
3.3%
9 41
 
1.7%
11 40
 
1.7%
Other values (140) 593
25.1%
ValueCountFrequency (%)
1 582
24.7%
2 337
14.3%
3 210
 
8.9%
4 160
 
6.8%
5 132
 
5.6%
6 95
 
4.0%
7 90
 
3.8%
8 77
 
3.3%
9 41
 
1.7%
10 29
 
1.2%
ValueCountFrequency (%)
10183 1
< 0.1%
1500 1
< 0.1%
999 1
< 0.1%
916 1
< 0.1%
853 1
< 0.1%
838 1
< 0.1%
719 1
< 0.1%
716 1
< 0.1%
668 1
< 0.1%
635 1
< 0.1%

title
Text

Distinct2357
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Memory size18.5 KiB
2023-10-17T19:32:38.218875image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length191
Median length107
Mean length32.59754
Min length3

Characters and Unicode

Total characters76865
Distinct characters460
Distinct categories16 ?
Distinct scripts15 ?
Distinct blocks16 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2356 ?
Unique (%)99.9%

Sample

1st rowHistoria de una prostituta vienesa
2nd row3 Segundos
3rd rowThe Photoshop Book for Digital Photographers
4th rowReaching Down the Rabbit Hole: Extraordinary Journeys into the Human Brain
5th rowAfrikaans hoort by Nederlands
ValueCountFrequency (%)
the 913
 
7.1%
of 451
 
3.5%
a 278
 
2.2%
and 238
 
1.8%
1 193
 
1.5%
in 148
 
1.1%
to 141
 
1.1%
2 127
 
1.0%
99
 
0.8%
for 84
 
0.7%
Other values (5619) 10201
79.2%
2023-10-17T19:32:38.853281image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10532
 
13.7%
e 6849
 
8.9%
o 4434
 
5.8%
a 4363
 
5.7%
i 4002
 
5.2%
n 3939
 
5.1%
r 3937
 
5.1%
t 3448
 
4.5%
s 3019
 
3.9%
l 2290
 
3.0%
Other values (450) 30052
39.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 50777
66.1%
Space Separator 10532
 
13.7%
Uppercase Letter 9872
 
12.8%
Other Punctuation 2014
 
2.6%
Other Letter 1404
 
1.8%
Decimal Number 961
 
1.3%
Close Punctuation 514
 
0.7%
Open Punctuation 514
 
0.7%
Dash Punctuation 189
 
0.2%
Nonspacing Mark 42
 
0.1%
Other values (6) 46
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
ا 184
 
13.1%
ل 123
 
8.8%
ي 80
 
5.7%
ر 74
 
5.3%
م 70
 
5.0%
ن 63
 
4.5%
ت 59
 
4.2%
و 55
 
3.9%
ة 44
 
3.1%
ب 39
 
2.8%
Other values (160) 613
43.7%
Lowercase Letter
ValueCountFrequency (%)
e 6849
13.5%
o 4434
 
8.7%
a 4363
 
8.6%
i 4002
 
7.9%
n 3939
 
7.8%
r 3937
 
7.8%
t 3448
 
6.8%
s 3019
 
5.9%
l 2290
 
4.5%
h 2150
 
4.2%
Other values (139) 12346
24.3%
Uppercase Letter
ValueCountFrequency (%)
T 1129
 
11.4%
S 906
 
9.2%
A 726
 
7.4%
B 659
 
6.7%
C 625
 
6.3%
M 545
 
5.5%
L 523
 
5.3%
H 493
 
5.0%
D 480
 
4.9%
P 456
 
4.6%
Other values (52) 3330
33.7%
Nonspacing Mark
ValueCountFrequency (%)
5
11.9%
4
 
9.5%
4
 
9.5%
4
 
9.5%
3
 
7.1%
َ 2
 
4.8%
ٌ 2
 
4.8%
2
 
4.8%
2
 
4.8%
2
 
4.8%
Other values (10) 12
28.6%
Other Punctuation
ValueCountFrequency (%)
, 547
27.2%
: 523
26.0%
# 451
22.4%
' 238
11.8%
. 132
 
6.6%
& 33
 
1.6%
! 33
 
1.6%
? 20
 
1.0%
/ 12
 
0.6%
" 8
 
0.4%
Other values (8) 17
 
0.8%
Spacing Mark
ValueCountFrequency (%)
10
30.3%
ি 3
 
9.1%
ி 3
 
9.1%
3
 
9.1%
2
 
6.1%
2
 
6.1%
2
 
6.1%
ി 2
 
6.1%
1
 
3.0%
1
 
3.0%
Other values (4) 4
 
12.1%
Decimal Number
ValueCountFrequency (%)
1 311
32.4%
2 182
18.9%
3 95
 
9.9%
0 84
 
8.7%
5 69
 
7.2%
4 62
 
6.5%
6 56
 
5.8%
8 35
 
3.6%
9 34
 
3.5%
7 29
 
3.0%
Other values (3) 4
 
0.4%
Math Symbol
ValueCountFrequency (%)
= 2
40.0%
| 2
40.0%
+ 1
20.0%
Close Punctuation
ValueCountFrequency (%)
) 508
98.8%
] 6
 
1.2%
Open Punctuation
ValueCountFrequency (%)
( 508
98.8%
[ 6
 
1.2%
Dash Punctuation
ValueCountFrequency (%)
- 185
97.9%
4
 
2.1%
Space Separator
ValueCountFrequency (%)
10532
100.0%
Final Punctuation
ValueCountFrequency (%)
5
100.0%
Format
ValueCountFrequency (%)
1
100.0%
Other Symbol
ValueCountFrequency (%)
° 1
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 60167
78.3%
Common 14732
 
19.2%
Arabic 1221
 
1.6%
Greek 299
 
0.4%
Cyrillic 183
 
0.2%
Bengali 68
 
0.1%
Thai 43
 
0.1%
Malayalam 32
 
< 0.1%
Han 26
 
< 0.1%
Devanagari 24
 
< 0.1%
Other values (5) 70
 
0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 6849
 
11.4%
o 4434
 
7.4%
a 4363
 
7.3%
i 4002
 
6.7%
n 3939
 
6.5%
r 3937
 
6.5%
t 3448
 
5.7%
s 3019
 
5.0%
l 2290
 
3.8%
h 2150
 
3.6%
Other values (119) 21736
36.1%
Arabic
ValueCountFrequency (%)
ا 184
15.1%
ل 123
 
10.1%
ي 80
 
6.6%
ر 74
 
6.1%
م 70
 
5.7%
ن 63
 
5.2%
ت 59
 
4.8%
و 55
 
4.5%
ة 44
 
3.6%
ب 39
 
3.2%
Other values (33) 430
35.2%
Greek
ValueCountFrequency (%)
α 30
 
10.0%
ι 22
 
7.4%
ο 20
 
6.7%
τ 19
 
6.4%
ρ 19
 
6.4%
κ 17
 
5.7%
η 14
 
4.7%
ς 13
 
4.3%
ν 12
 
4.0%
σ 12
 
4.0%
Other values (33) 121
40.5%
Common
ValueCountFrequency (%)
10532
71.5%
, 547
 
3.7%
: 523
 
3.6%
) 508
 
3.4%
( 508
 
3.4%
# 451
 
3.1%
1 311
 
2.1%
' 238
 
1.6%
- 185
 
1.3%
2 182
 
1.2%
Other values (31) 747
 
5.1%
Cyrillic
ValueCountFrequency (%)
е 20
 
10.9%
а 16
 
8.7%
н 14
 
7.7%
т 13
 
7.1%
и 12
 
6.6%
о 11
 
6.0%
л 9
 
4.9%
к 9
 
4.9%
р 8
 
4.4%
с 7
 
3.8%
Other values (29) 64
35.0%
Bengali
ValueCountFrequency (%)
10
 
14.7%
5
 
7.4%
4
 
5.9%
4
 
5.9%
4
 
5.9%
3
 
4.4%
ি 3
 
4.4%
3
 
4.4%
3
 
4.4%
3
 
4.4%
Other values (21) 26
38.2%
Han
ValueCountFrequency (%)
2
 
7.7%
2
 
7.7%
1
 
3.8%
1
 
3.8%
1
 
3.8%
1
 
3.8%
1
 
3.8%
1
 
3.8%
1
 
3.8%
1
 
3.8%
Other values (14) 14
53.8%
Thai
ValueCountFrequency (%)
5
 
11.6%
5
 
11.6%
4
 
9.3%
3
 
7.0%
2
 
4.7%
2
 
4.7%
2
 
4.7%
2
 
4.7%
2
 
4.7%
2
 
4.7%
Other values (13) 14
32.6%
Malayalam
ValueCountFrequency (%)
5
15.6%
2
 
6.2%
2
 
6.2%
2
 
6.2%
2
 
6.2%
2
 
6.2%
ി 2
 
6.2%
1
 
3.1%
1
 
3.1%
1
 
3.1%
Other values (12) 12
37.5%
Devanagari
ValueCountFrequency (%)
3
12.5%
2
 
8.3%
2
 
8.3%
2
 
8.3%
2
 
8.3%
2
 
8.3%
2
 
8.3%
2
 
8.3%
1
 
4.2%
1
 
4.2%
Other values (5) 5
20.8%
Tamil
ValueCountFrequency (%)
4
17.4%
ி 3
13.0%
2
8.7%
2
8.7%
2
8.7%
2
8.7%
1
 
4.3%
1
 
4.3%
1
 
4.3%
1
 
4.3%
Other values (4) 4
17.4%
Hebrew
ValueCountFrequency (%)
י 3
15.8%
ע 3
15.8%
ו 2
10.5%
ד 2
10.5%
ם 2
10.5%
ל 1
 
5.3%
ר 1
 
5.3%
ק 1
 
5.3%
מ 1
 
5.3%
ת 1
 
5.3%
Other values (2) 2
10.5%
Hiragana
ValueCountFrequency (%)
3
27.3%
1
 
9.1%
1
 
9.1%
1
 
9.1%
1
 
9.1%
1
 
9.1%
1
 
9.1%
1
 
9.1%
1
 
9.1%
Hangul
ValueCountFrequency (%)
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
Inherited
ValueCountFrequency (%)
َ 2
25.0%
ٌ 2
25.0%
ِ 1
12.5%
ّ 1
12.5%
1
12.5%
́ 1
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 74635
97.1%
Arabic 1230
 
1.6%
None 534
 
0.7%
Cyrillic 183
 
0.2%
Bengali 68
 
0.1%
Thai 43
 
0.1%
Malayalam 32
 
< 0.1%
CJK 26
 
< 0.1%
Devanagari 24
 
< 0.1%
Tamil 23
 
< 0.1%
Other values (6) 67
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
10532
 
14.1%
e 6849
 
9.2%
o 4434
 
5.9%
a 4363
 
5.8%
i 4002
 
5.4%
n 3939
 
5.3%
r 3937
 
5.3%
t 3448
 
4.6%
s 3019
 
4.0%
l 2290
 
3.1%
Other values (76) 27822
37.3%
Arabic
ValueCountFrequency (%)
ا 184
15.0%
ل 123
 
10.0%
ي 80
 
6.5%
ر 74
 
6.0%
م 70
 
5.7%
ن 63
 
5.1%
ت 59
 
4.8%
و 55
 
4.5%
ة 44
 
3.6%
ب 39
 
3.2%
Other values (38) 439
35.7%
None
ValueCountFrequency (%)
α 30
 
5.6%
é 23
 
4.3%
ι 22
 
4.1%
ο 20
 
3.7%
í 19
 
3.6%
τ 19
 
3.6%
ρ 19
 
3.6%
κ 17
 
3.2%
ü 15
 
2.8%
η 14
 
2.6%
Other values (100) 336
62.9%
Cyrillic
ValueCountFrequency (%)
е 20
 
10.9%
а 16
 
8.7%
н 14
 
7.7%
т 13
 
7.1%
и 12
 
6.6%
о 11
 
6.0%
л 9
 
4.9%
к 9
 
4.9%
р 8
 
4.4%
с 7
 
3.8%
Other values (29) 64
35.0%
Bengali
ValueCountFrequency (%)
10
 
14.7%
5
 
7.4%
4
 
5.9%
4
 
5.9%
4
 
5.9%
3
 
4.4%
ি 3
 
4.4%
3
 
4.4%
3
 
4.4%
3
 
4.4%
Other values (21) 26
38.2%
Punctuation
ValueCountFrequency (%)
5
50.0%
4
40.0%
1
 
10.0%
Thai
ValueCountFrequency (%)
5
 
11.6%
5
 
11.6%
4
 
9.3%
3
 
7.0%
2
 
4.7%
2
 
4.7%
2
 
4.7%
2
 
4.7%
2
 
4.7%
2
 
4.7%
Other values (13) 14
32.6%
Malayalam
ValueCountFrequency (%)
5
15.6%
2
 
6.2%
2
 
6.2%
2
 
6.2%
2
 
6.2%
2
 
6.2%
ി 2
 
6.2%
1
 
3.1%
1
 
3.1%
1
 
3.1%
Other values (12) 12
37.5%
Tamil
ValueCountFrequency (%)
4
17.4%
ி 3
13.0%
2
8.7%
2
8.7%
2
8.7%
2
8.7%
1
 
4.3%
1
 
4.3%
1
 
4.3%
1
 
4.3%
Other values (4) 4
17.4%
Hebrew
ValueCountFrequency (%)
י 3
15.8%
ע 3
15.8%
ו 2
10.5%
ד 2
10.5%
ם 2
10.5%
ל 1
 
5.3%
ר 1
 
5.3%
ק 1
 
5.3%
מ 1
 
5.3%
ת 1
 
5.3%
Other values (2) 2
10.5%
Hiragana
ValueCountFrequency (%)
3
27.3%
1
 
9.1%
1
 
9.1%
1
 
9.1%
1
 
9.1%
1
 
9.1%
1
 
9.1%
1
 
9.1%
1
 
9.1%
Devanagari
ValueCountFrequency (%)
3
12.5%
2
 
8.3%
2
 
8.3%
2
 
8.3%
2
 
8.3%
2
 
8.3%
2
 
8.3%
2
 
8.3%
1
 
4.2%
1
 
4.2%
Other values (5) 5
20.8%
Latin Ext Additional
ValueCountFrequency (%)
2
11.8%
2
11.8%
2
11.8%
1
 
5.9%
1
 
5.9%
ế 1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
Other values (4) 4
23.5%
CJK
ValueCountFrequency (%)
2
 
7.7%
2
 
7.7%
1
 
3.8%
1
 
3.8%
1
 
3.8%
1
 
3.8%
1
 
3.8%
1
 
3.8%
1
 
3.8%
1
 
3.8%
Other values (14) 14
53.8%
Hangul
ValueCountFrequency (%)
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
Diacriticals
ValueCountFrequency (%)
́ 1
100.0%
Distinct2357
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Memory size18.5 KiB
2023-10-17T19:32:39.235755image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length191
Median length107
Mean length32.59754
Min length3

Characters and Unicode

Total characters76865
Distinct characters460
Distinct categories16 ?
Distinct scripts15 ?
Distinct blocks16 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2356 ?
Unique (%)99.9%

Sample

1st rowHistoria de una prostituta vienesa
2nd row3 Segundos
3rd rowThe Photoshop Book for Digital Photographers
4th rowReaching Down the Rabbit Hole: Extraordinary Journeys into the Human Brain
5th rowAfrikaans hoort by Nederlands
ValueCountFrequency (%)
the 913
 
7.1%
of 451
 
3.5%
a 278
 
2.2%
and 238
 
1.8%
1 193
 
1.5%
in 148
 
1.1%
to 141
 
1.1%
2 127
 
1.0%
99
 
0.8%
for 84
 
0.7%
Other values (5619) 10201
79.2%
2023-10-17T19:32:39.932983image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10532
 
13.7%
e 6849
 
8.9%
o 4434
 
5.8%
a 4363
 
5.7%
i 4002
 
5.2%
n 3939
 
5.1%
r 3937
 
5.1%
t 3448
 
4.5%
s 3019
 
3.9%
l 2290
 
3.0%
Other values (450) 30052
39.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 50777
66.1%
Space Separator 10532
 
13.7%
Uppercase Letter 9872
 
12.8%
Other Punctuation 2014
 
2.6%
Other Letter 1404
 
1.8%
Decimal Number 961
 
1.3%
Close Punctuation 514
 
0.7%
Open Punctuation 514
 
0.7%
Dash Punctuation 189
 
0.2%
Nonspacing Mark 42
 
0.1%
Other values (6) 46
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
ا 184
 
13.1%
ل 123
 
8.8%
ي 80
 
5.7%
ر 74
 
5.3%
م 70
 
5.0%
ن 63
 
4.5%
ت 59
 
4.2%
و 55
 
3.9%
ة 44
 
3.1%
ب 39
 
2.8%
Other values (160) 613
43.7%
Lowercase Letter
ValueCountFrequency (%)
e 6849
13.5%
o 4434
 
8.7%
a 4363
 
8.6%
i 4002
 
7.9%
n 3939
 
7.8%
r 3937
 
7.8%
t 3448
 
6.8%
s 3019
 
5.9%
l 2290
 
4.5%
h 2150
 
4.2%
Other values (139) 12346
24.3%
Uppercase Letter
ValueCountFrequency (%)
T 1129
 
11.4%
S 906
 
9.2%
A 726
 
7.4%
B 659
 
6.7%
C 625
 
6.3%
M 545
 
5.5%
L 523
 
5.3%
H 493
 
5.0%
D 480
 
4.9%
P 456
 
4.6%
Other values (52) 3330
33.7%
Nonspacing Mark
ValueCountFrequency (%)
5
11.9%
4
 
9.5%
4
 
9.5%
4
 
9.5%
3
 
7.1%
َ 2
 
4.8%
ٌ 2
 
4.8%
2
 
4.8%
2
 
4.8%
2
 
4.8%
Other values (10) 12
28.6%
Other Punctuation
ValueCountFrequency (%)
, 547
27.2%
: 523
26.0%
# 451
22.4%
' 238
11.8%
. 132
 
6.6%
& 33
 
1.6%
! 33
 
1.6%
? 20
 
1.0%
/ 12
 
0.6%
" 8
 
0.4%
Other values (8) 17
 
0.8%
Spacing Mark
ValueCountFrequency (%)
10
30.3%
ি 3
 
9.1%
ி 3
 
9.1%
3
 
9.1%
2
 
6.1%
2
 
6.1%
2
 
6.1%
ി 2
 
6.1%
1
 
3.0%
1
 
3.0%
Other values (4) 4
 
12.1%
Decimal Number
ValueCountFrequency (%)
1 311
32.4%
2 182
18.9%
3 95
 
9.9%
0 84
 
8.7%
5 69
 
7.2%
4 62
 
6.5%
6 56
 
5.8%
8 35
 
3.6%
9 34
 
3.5%
7 29
 
3.0%
Other values (3) 4
 
0.4%
Math Symbol
ValueCountFrequency (%)
= 2
40.0%
| 2
40.0%
+ 1
20.0%
Close Punctuation
ValueCountFrequency (%)
) 508
98.8%
] 6
 
1.2%
Open Punctuation
ValueCountFrequency (%)
( 508
98.8%
[ 6
 
1.2%
Dash Punctuation
ValueCountFrequency (%)
- 185
97.9%
4
 
2.1%
Space Separator
ValueCountFrequency (%)
10532
100.0%
Final Punctuation
ValueCountFrequency (%)
5
100.0%
Format
ValueCountFrequency (%)
1
100.0%
Other Symbol
ValueCountFrequency (%)
° 1
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 60167
78.3%
Common 14732
 
19.2%
Arabic 1221
 
1.6%
Greek 299
 
0.4%
Cyrillic 183
 
0.2%
Bengali 68
 
0.1%
Thai 43
 
0.1%
Malayalam 32
 
< 0.1%
Han 26
 
< 0.1%
Devanagari 24
 
< 0.1%
Other values (5) 70
 
0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 6849
 
11.4%
o 4434
 
7.4%
a 4363
 
7.3%
i 4002
 
6.7%
n 3939
 
6.5%
r 3937
 
6.5%
t 3448
 
5.7%
s 3019
 
5.0%
l 2290
 
3.8%
h 2150
 
3.6%
Other values (119) 21736
36.1%
Arabic
ValueCountFrequency (%)
ا 184
15.1%
ل 123
 
10.1%
ي 80
 
6.6%
ر 74
 
6.1%
م 70
 
5.7%
ن 63
 
5.2%
ت 59
 
4.8%
و 55
 
4.5%
ة 44
 
3.6%
ب 39
 
3.2%
Other values (33) 430
35.2%
Greek
ValueCountFrequency (%)
α 30
 
10.0%
ι 22
 
7.4%
ο 20
 
6.7%
τ 19
 
6.4%
ρ 19
 
6.4%
κ 17
 
5.7%
η 14
 
4.7%
ς 13
 
4.3%
ν 12
 
4.0%
σ 12
 
4.0%
Other values (33) 121
40.5%
Common
ValueCountFrequency (%)
10532
71.5%
, 547
 
3.7%
: 523
 
3.6%
) 508
 
3.4%
( 508
 
3.4%
# 451
 
3.1%
1 311
 
2.1%
' 238
 
1.6%
- 185
 
1.3%
2 182
 
1.2%
Other values (31) 747
 
5.1%
Cyrillic
ValueCountFrequency (%)
е 20
 
10.9%
а 16
 
8.7%
н 14
 
7.7%
т 13
 
7.1%
и 12
 
6.6%
о 11
 
6.0%
л 9
 
4.9%
к 9
 
4.9%
р 8
 
4.4%
с 7
 
3.8%
Other values (29) 64
35.0%
Bengali
ValueCountFrequency (%)
10
 
14.7%
5
 
7.4%
4
 
5.9%
4
 
5.9%
4
 
5.9%
3
 
4.4%
ি 3
 
4.4%
3
 
4.4%
3
 
4.4%
3
 
4.4%
Other values (21) 26
38.2%
Han
ValueCountFrequency (%)
2
 
7.7%
2
 
7.7%
1
 
3.8%
1
 
3.8%
1
 
3.8%
1
 
3.8%
1
 
3.8%
1
 
3.8%
1
 
3.8%
1
 
3.8%
Other values (14) 14
53.8%
Thai
ValueCountFrequency (%)
5
 
11.6%
5
 
11.6%
4
 
9.3%
3
 
7.0%
2
 
4.7%
2
 
4.7%
2
 
4.7%
2
 
4.7%
2
 
4.7%
2
 
4.7%
Other values (13) 14
32.6%
Malayalam
ValueCountFrequency (%)
5
15.6%
2
 
6.2%
2
 
6.2%
2
 
6.2%
2
 
6.2%
2
 
6.2%
ി 2
 
6.2%
1
 
3.1%
1
 
3.1%
1
 
3.1%
Other values (12) 12
37.5%
Devanagari
ValueCountFrequency (%)
3
12.5%
2
 
8.3%
2
 
8.3%
2
 
8.3%
2
 
8.3%
2
 
8.3%
2
 
8.3%
2
 
8.3%
1
 
4.2%
1
 
4.2%
Other values (5) 5
20.8%
Tamil
ValueCountFrequency (%)
4
17.4%
ி 3
13.0%
2
8.7%
2
8.7%
2
8.7%
2
8.7%
1
 
4.3%
1
 
4.3%
1
 
4.3%
1
 
4.3%
Other values (4) 4
17.4%
Hebrew
ValueCountFrequency (%)
י 3
15.8%
ע 3
15.8%
ו 2
10.5%
ד 2
10.5%
ם 2
10.5%
ל 1
 
5.3%
ר 1
 
5.3%
ק 1
 
5.3%
מ 1
 
5.3%
ת 1
 
5.3%
Other values (2) 2
10.5%
Hiragana
ValueCountFrequency (%)
3
27.3%
1
 
9.1%
1
 
9.1%
1
 
9.1%
1
 
9.1%
1
 
9.1%
1
 
9.1%
1
 
9.1%
1
 
9.1%
Hangul
ValueCountFrequency (%)
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
Inherited
ValueCountFrequency (%)
َ 2
25.0%
ٌ 2
25.0%
ِ 1
12.5%
ّ 1
12.5%
1
12.5%
́ 1
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 74635
97.1%
Arabic 1230
 
1.6%
None 534
 
0.7%
Cyrillic 183
 
0.2%
Bengali 68
 
0.1%
Thai 43
 
0.1%
Malayalam 32
 
< 0.1%
CJK 26
 
< 0.1%
Devanagari 24
 
< 0.1%
Tamil 23
 
< 0.1%
Other values (6) 67
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
10532
 
14.1%
e 6849
 
9.2%
o 4434
 
5.9%
a 4363
 
5.8%
i 4002
 
5.4%
n 3939
 
5.3%
r 3937
 
5.3%
t 3448
 
4.6%
s 3019
 
4.0%
l 2290
 
3.1%
Other values (76) 27822
37.3%
Arabic
ValueCountFrequency (%)
ا 184
15.0%
ل 123
 
10.0%
ي 80
 
6.5%
ر 74
 
6.0%
م 70
 
5.7%
ن 63
 
5.1%
ت 59
 
4.8%
و 55
 
4.5%
ة 44
 
3.6%
ب 39
 
3.2%
Other values (38) 439
35.7%
None
ValueCountFrequency (%)
α 30
 
5.6%
é 23
 
4.3%
ι 22
 
4.1%
ο 20
 
3.7%
í 19
 
3.6%
τ 19
 
3.6%
ρ 19
 
3.6%
κ 17
 
3.2%
ü 15
 
2.8%
η 14
 
2.6%
Other values (100) 336
62.9%
Cyrillic
ValueCountFrequency (%)
е 20
 
10.9%
а 16
 
8.7%
н 14
 
7.7%
т 13
 
7.1%
и 12
 
6.6%
о 11
 
6.0%
л 9
 
4.9%
к 9
 
4.9%
р 8
 
4.4%
с 7
 
3.8%
Other values (29) 64
35.0%
Bengali
ValueCountFrequency (%)
10
 
14.7%
5
 
7.4%
4
 
5.9%
4
 
5.9%
4
 
5.9%
3
 
4.4%
ি 3
 
4.4%
3
 
4.4%
3
 
4.4%
3
 
4.4%
Other values (21) 26
38.2%
Punctuation
ValueCountFrequency (%)
5
50.0%
4
40.0%
1
 
10.0%
Thai
ValueCountFrequency (%)
5
 
11.6%
5
 
11.6%
4
 
9.3%
3
 
7.0%
2
 
4.7%
2
 
4.7%
2
 
4.7%
2
 
4.7%
2
 
4.7%
2
 
4.7%
Other values (13) 14
32.6%
Malayalam
ValueCountFrequency (%)
5
15.6%
2
 
6.2%
2
 
6.2%
2
 
6.2%
2
 
6.2%
2
 
6.2%
ി 2
 
6.2%
1
 
3.1%
1
 
3.1%
1
 
3.1%
Other values (12) 12
37.5%
Tamil
ValueCountFrequency (%)
4
17.4%
ி 3
13.0%
2
8.7%
2
8.7%
2
8.7%
2
8.7%
1
 
4.3%
1
 
4.3%
1
 
4.3%
1
 
4.3%
Other values (4) 4
17.4%
Hebrew
ValueCountFrequency (%)
י 3
15.8%
ע 3
15.8%
ו 2
10.5%
ד 2
10.5%
ם 2
10.5%
ל 1
 
5.3%
ר 1
 
5.3%
ק 1
 
5.3%
מ 1
 
5.3%
ת 1
 
5.3%
Other values (2) 2
10.5%
Hiragana
ValueCountFrequency (%)
3
27.3%
1
 
9.1%
1
 
9.1%
1
 
9.1%
1
 
9.1%
1
 
9.1%
1
 
9.1%
1
 
9.1%
1
 
9.1%
Devanagari
ValueCountFrequency (%)
3
12.5%
2
 
8.3%
2
 
8.3%
2
 
8.3%
2
 
8.3%
2
 
8.3%
2
 
8.3%
2
 
8.3%
1
 
4.2%
1
 
4.2%
Other values (5) 5
20.8%
Latin Ext Additional
ValueCountFrequency (%)
2
11.8%
2
11.8%
2
11.8%
1
 
5.9%
1
 
5.9%
ế 1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
Other values (4) 4
23.5%
CJK
ValueCountFrequency (%)
2
 
7.7%
2
 
7.7%
1
 
3.8%
1
 
3.8%
1
 
3.8%
1
 
3.8%
1
 
3.8%
1
 
3.8%
1
 
3.8%
1
 
3.8%
Other values (14) 14
53.8%
Hangul
ValueCountFrequency (%)
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
Diacriticals
ValueCountFrequency (%)
́ 1
100.0%

url
Text

Distinct2358
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size18.5 KiB
2023-10-17T19:32:40.260767image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length133
Median length109
Mean length63.085242
Min length0

Characters and Unicode

Total characters148755
Distinct characters66
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2358 ?
Unique (%)100.0%

Sample

1st rowhttps://www.goodreads.com/book/show/22554103-historia-de-una-prostituta-vienesa
2nd rowhttps://www.goodreads.com/book/show/15829792-3-segundos
3rd rowhttps://www.goodreads.com/book/show/92838.The_Photoshop_Book_for_Digital_Photographers
4th rowhttps://www.goodreads.com/book/show/23460726-reaching-down-the-rabbit-hole
5th rowhttps://www.goodreads.com/book/show/27983357-afrikaans-hoort-by-nederlands
ValueCountFrequency (%)
https://www.goodreads.com/book/show/22554103-historia-de-una-prostituta-vienesa 1
 
< 0.1%
https://www.goodreads.com/book/show/30634831-devlin-s-daughter 1
 
< 0.1%
https://www.goodreads.com/book/show/18206694-women-and-fitness-in-american-culture 1
 
< 0.1%
https://www.goodreads.com/book/show/92838.the_photoshop_book_for_digital_photographers 1
 
< 0.1%
https://www.goodreads.com/book/show/23460726-reaching-down-the-rabbit-hole 1
 
< 0.1%
https://www.goodreads.com/book/show/27983357-afrikaans-hoort-by-nederlands 1
 
< 0.1%
https://www.goodreads.com/book/show/9368172-the-mystery-of-the-hidden-driveway 1
 
< 0.1%
https://www.goodreads.com/book/show/13227511-the-man-with-the-bionic-brain 1
 
< 0.1%
https://www.goodreads.com/book/show/3379686-vivienne-westwood 1
 
< 0.1%
https://www.goodreads.com/book/show/23273757-tainted 1
 
< 0.1%
Other values (2347) 2347
99.6%
2023-10-17T19:32:40.839907image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 16992
 
11.4%
/ 11785
 
7.9%
w 9887
 
6.6%
s 9424
 
6.3%
t 7430
 
5.0%
e 6833
 
4.6%
- 6542
 
4.4%
h 6387
 
4.3%
d 6125
 
4.1%
a 5477
 
3.7%
Other values (56) 61873
41.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 102480
68.9%
Other Punctuation 19289
 
13.0%
Decimal Number 17983
 
12.1%
Dash Punctuation 6542
 
4.4%
Uppercase Letter 1275
 
0.9%
Connector Punctuation 1186
 
0.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 16992
16.6%
w 9887
 
9.6%
s 9424
 
9.2%
t 7430
 
7.3%
e 6833
 
6.7%
h 6387
 
6.2%
d 6125
 
6.0%
a 5477
 
5.3%
r 4952
 
4.8%
c 3378
 
3.3%
Other values (16) 25595
25.0%
Uppercase Letter
ValueCountFrequency (%)
T 162
 
12.7%
S 127
 
10.0%
C 90
 
7.1%
W 78
 
6.1%
A 77
 
6.0%
B 77
 
6.0%
M 72
 
5.6%
L 61
 
4.8%
H 60
 
4.7%
G 54
 
4.2%
Other values (15) 417
32.7%
Decimal Number
ValueCountFrequency (%)
1 2456
13.7%
2 2315
12.9%
3 1999
11.1%
7 1720
9.6%
6 1621
9.0%
8 1611
9.0%
5 1610
9.0%
0 1574
8.8%
4 1559
8.7%
9 1518
8.4%
Other Punctuation
ValueCountFrequency (%)
/ 11785
61.1%
. 5147
26.7%
: 2357
 
12.2%
Dash Punctuation
ValueCountFrequency (%)
- 6542
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1186
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 103755
69.7%
Common 45000
30.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 16992
16.4%
w 9887
 
9.5%
s 9424
 
9.1%
t 7430
 
7.2%
e 6833
 
6.6%
h 6387
 
6.2%
d 6125
 
5.9%
a 5477
 
5.3%
r 4952
 
4.8%
c 3378
 
3.3%
Other values (41) 26870
25.9%
Common
ValueCountFrequency (%)
/ 11785
26.2%
- 6542
14.5%
. 5147
11.4%
1 2456
 
5.5%
: 2357
 
5.2%
2 2315
 
5.1%
3 1999
 
4.4%
7 1720
 
3.8%
6 1621
 
3.6%
8 1611
 
3.6%
Other values (5) 7447
16.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 148755
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 16992
 
11.4%
/ 11785
 
7.9%
w 9887
 
6.6%
s 9424
 
6.3%
t 7430
 
5.0%
e 6833
 
4.6%
- 6542
 
4.4%
h 6387
 
4.3%
d 6125
 
4.1%
a 5477
 
3.7%
Other values (56) 61873
41.6%
Distinct2351
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Memory size18.5 KiB
2023-10-17T19:32:41.191559image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.427905
Min length0

Characters and Unicode

Total characters17515
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2344 ?
Unique (%)99.4%

Sample

1st row843363
2nd row18026505
3rd row42022604
4th row27334735
5th row47985533
ValueCountFrequency (%)
23596 2
 
0.1%
3324344 2
 
0.1%
47262458 2
 
0.1%
25491300 2
 
0.1%
1565818 2
 
0.1%
17127576 2
 
0.1%
2977639 2
 
0.1%
18419319 1
 
< 0.1%
54869921 1
 
< 0.1%
16669337 1
 
< 0.1%
Other values (2340) 2340
99.3%
2023-10-17T19:32:41.720160image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 2135
12.2%
2 2082
11.9%
4 2055
11.7%
5 1843
10.5%
3 1747
10.0%
6 1642
9.4%
7 1571
9.0%
9 1521
8.7%
8 1477
8.4%
0 1442
8.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 17515
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 2135
12.2%
2 2082
11.9%
4 2055
11.7%
5 1843
10.5%
3 1747
10.0%
6 1642
9.4%
7 1571
9.0%
9 1521
8.7%
8 1477
8.4%
0 1442
8.2%

Most occurring scripts

ValueCountFrequency (%)
Common 17515
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 2135
12.2%
2 2082
11.9%
4 2055
11.7%
5 1843
10.5%
3 1747
10.0%
6 1642
9.4%
7 1571
9.0%
9 1521
8.7%
8 1477
8.4%
0 1442
8.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17515
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 2135
12.2%
2 2082
11.9%
4 2055
11.7%
5 1843
10.5%
3 1747
10.0%
6 1642
9.4%
7 1571
9.0%
9 1521
8.7%
8 1477
8.4%
0 1442
8.2%

Interactions

2023-10-17T19:32:10.537596image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-10-17T19:30:47.133472image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-10-17T19:31:03.489786image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-10-17T19:31:55.039091image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-10-17T19:32:10.683251image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-10-17T19:30:47.353184image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-10-17T19:31:13.312721image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-10-17T19:31:55.155615image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-10-17T19:32:25.969250image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-10-17T19:31:03.179875image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-10-17T19:31:36.520382image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-10-17T19:32:10.278512image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-10-17T19:32:26.094295image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-10-17T19:31:03.327335image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-10-17T19:31:45.455431image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-10-17T19:32:10.424517image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Correlations

2023-10-17T19:32:41.909391image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
average_ratingbook_idratings_counttext_reviews_countcountry_codeformatis_ebookpublication_daypublication_month
average_rating1.0000.0060.0200.0361.0000.0910.0610.0000.000
book_id0.0061.0000.0290.0211.0001.0001.0001.0001.000
ratings_count0.0200.0291.0000.8621.0000.0000.0000.0890.043
text_reviews_count0.0360.0210.8621.0001.0000.0000.0000.1410.064
country_code1.0001.0001.0001.0001.0000.0001.0000.0000.000
format0.0911.0000.0000.0000.0001.0000.5730.1080.188
is_ebook0.0611.0000.0000.0001.0000.5731.0000.1270.132
publication_day0.0001.0000.0890.1410.0000.1080.1271.0000.272
publication_month0.0001.0000.0430.0640.0000.1880.1320.2721.000

Missing values

2023-10-17T19:32:26.367619image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
A simple visualization of nullity by column.
2023-10-17T19:32:26.815188image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2023-10-17T19:32:27.053093image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

asinauthorsaverage_ratingbook_idcountry_codedescriptionedition_informationformatimage_urlis_ebookisbnisbn13kindle_asinlanguage_codelinknum_pagespopular_shelvespublication_daypublication_monthpublication_yearpublisherratings_countseriessimilar_bookstext_reviews_counttitletitle_without_seriesurlwork_id
0[(262262, )]3.2422554103USAproximadamente en las mismas fechas en que escribia sus memorias esta prostituta vienesa, tambien redactaba las suyas, igualmente apasionantes, la gran cantante wagneriana Wilhelmine Shroeder-Devrient, autora de Memorias de una cantante alemana. Si esta fue una mujer refinada, culta y rica, aquella tuvo un origen humilde y fue precisamente gracias a la profesion mas antigua del mundo como adquirio modales y conocimientos suficientes como para poder redactar con acierto, ya al final de su vida, este extraordinario testimonio personal, escalofriante por su sinceridad, que entrego a su medico unas semanas antes de someterse a una grave operacion. Estas confesiones intimas de una prostituta no tienen tan solo el valor testimonial directo de una actividad en y por principio inconfesable, sino tambien el de ilustrar con todo lujo de detalles la vida amorosa de la sociedad vienesa de la segunda mitad del siglo XIX. Por eso sus primeros editores alemanes procuraron respetar al maximo el texto original.Hardcoverhttps://images.gr-assets.com/books/1403253289m/22554103.jpgfalse8422669552spahttps://www.goodreads.com/book/show/22554103-historia-de-una-prostituta-vienesa270[(133, to-read), (6, erotic), (5, erotica), (3, 1), (2, favorites), (2, sex), (2, e-book), (2, books-i-own), (2, erotika), (2, translated), (2, vienna), (2, sexuality), (2, default), (2, deutsch), (1, other-owned), (1, Österreich), (1, verfilmt), (1, biographien), (1, l-érotisme), (1, nope), (1, sonrisa-vertical-coleccion), (1, coleccion), (1, passion), (1, currently-reading), (1, austrohongaresa), (1, sprache-ger), (1, klassiker), (1, zu-verschenken), (1, from-library), (1, fiction), (1, thriller), (1, to-sort), (1, 06-10), (1, did-not-finish), (1, owned-books), (1, audio), (1, luetut-2007), (1, classics-european), (1, rated-oh), (1, wien), (1, bingo-2016), (1, erotic-sex), (1, genre-fiction), (1, my-books), (1, have-tbr), (1, e-books), (1, read-translations), (1, zzfixme-pedantic), (1, might-read), (1, zzz-lang-german), (1, 15-07), (1, possible-summer-reads), (1, maybe), (1, s-xx), (1, literatura-austriaca), (1, erotisme), (1, decepcionant-soporífer), (1, german-literature), (1, sonrisa-vertical), (1, sexual), (1, topic), (1, promotes-incest), (1, do-not-read), (1, 2fiction), (1, 1ebook), (1, biographical-novel), (1, best-rating), (1, top), (1, miscellaneous), (1, biographie-erinnerungen), (1, oesterreich-ungarn), (1, adjust-edition), (1, add-cover), (1, vertical), (1, german), (1, buy), (1, too-sexy-for-maiden-aunts), (1, published-1906), (1, austria), (1, book), (1, own-it-not-yet-read), (1, autobiography), (1, c19), (1, prostitution), (1, interlibrary-loans), (1, my-library), (1, trashy), (1, smut), (1, pedophilia), (1, biography-memoirs), (1, historical), (1, hrrrmpf)]1998Circulo de lectores7.0[][119534, 3689628, 17251278, 1508991, 35259261, 9439857, 597293, 8800795, 294624, 3071773, 1938099, 2100487, 953345, 989060, 1603221]3.0Historia de una prostituta vienesaHistoria de una prostituta vienesahttps://www.goodreads.com/book/show/22554103-historia-de-una-prostituta-vienesa843363
1[(329097, )]4.0115829792USHardcoverhttps://images.gr-assets.com/books/1345041681m/15829792.jpgfalse84967221259788496722125spahttps://www.goodreads.com/book/show/15829792-3-segundos72[(86, to-read), (12, bd), (8, comics), (5, graphic-novels), (4, graphic-novel), (3, wordless), (3, owned), (3, comic), (2, french), (2, français), (2, art), (2, default), (2, fiction), (1, speculative-fiction-comics), (1, checked), (1, books-i-own), (1, comix), (1, lido-en-castelan), (1, banda-deseñada-francesa), (1, thriller), (1, gift), (1, comic-book), (1, graphic-novels-and-illustrated), (1, 2016-graphic), (1, anobii), (1, bd-graphic-novels), (1, 2015-comics), (1, souhaités), (1, 2015-bd), (1, unitario), (1, ed-esp), (1, silent), (1, fav), (1, comics-wishlist), (1, strongly-recommend), (1, graphics), (1, to-acquire), (1, graphic-novel-manga-and-comic), (1, florent), (1, muda), (1, mathieu), (1, historieta), (1, francia), (1, experimental), (1, accorsi), (1, 2010s), (1, bds), (1, en-francés), (1, graphic-storytelling), (1, comics-manga), (1, unshelved), (1, verythoughtprovoking), (1, bds-read), (1, to-read-hq), (1, my-favourite-graphic-novels), (1, comics-para-buscar), (1, taula), (1, graphicnovels), (1, comic-altres), (1, fr), (1, bm), (1, dans-ma-biblio), (1, spanish), (1, crime), (1, comics-bd), (1, crime_mystère), (1, bd_comic_manga)]32012Ediciones Sinsentido11.0[][]2.03 Segundos3 Segundoshttps://www.goodreads.com/book/show/15829792-3-segundos18026505
2[(53283, )]4.0692838USThis is a workflow-based, time-saving handbook for the digital photography professional. Coverage is aimed squarely at the professional photographer who is making the switch from traditional to digital photography.Paperbackhttps://s.gr-assets.com/assets/nophoto/book/111x148-bcc042a9c91a29c1d680899eff700a03.pngfalse07357123609780735712362B006OJ42PUhttps://www.goodreads.com/book/show/92838.The_Photoshop_Book_for_Digital_Photographers358[(40, to-read), (14, photography), (4, reference), (3, photoshop), (3, graphic-design), (3, computers), (2, owned), (2, nonfiction), (1, biblioteca), (1, 46-photography), (1, b), (1, periodicals), (1, read-2015), (1, design), (1, non-fiction), (1, currently-reading), (1, computer-books), (1, topic-arts-graphic-arts), (1, to-own), (1, technology), (1, source-owned), (1, sell), (1, reference-digital), (1, owned-books), (1, old-books), (1, obsolete), (1, lent), (1, imaging-ps), (1, how-tos), (1, home), (1, hobbies), (1, have), (1, find-etext), (1, diy), (1, contemporary), (1, bedroom-case-01-shelf-02), (1, art), (1, 20th-century)]532003New Riders Publishing70.0[][]3.0The Photoshop Book for Digital PhotographersThe Photoshop Book for Digital Photographershttps://www.goodreads.com/book/show/92838.The_Photoshop_Book_for_Digital_Photographers42022604
3B00LRHW99U[(717599, ), (9805607, )]3.9823460726US"Tell the doctor where it hurts." It sounds simple enough, unless the problem affects the very organ that produces awareness and generates speech. What is it like to try to heal the body when the mind is under attack? In this book, Dr. Allan Ropper and Brian Burrell take the reader behind the scenes at Harvard Medical School's neurology unit to show how a seasoned diagnostician faces down bizarre, life-altering afflictions. Like Alice in Wonderland, Dr. Ropper inhabits a world where absurdities abound:* A figure skater whose body has become a ticking time-bomb\n* A salesman who drives around and around a traffic rotary, unable to get off\n* A college quarterback who can't stop calling the same play\n* A child molester who, after falling on the ice, is left with a brain that is very much dead inside a body that is very much alive\n* A mother of two young girls, diagnosed with ALS, who has to decide whether a life locked inside her own head is worth livingHow does one begin to treat such cases, to counsel people whose lives may be changed forever? How does one train the next generation of clinicians to deal with the moral and medical aspects of brain disease? Dr. Ropper and his colleague answer these questions by taking the reader into a rarified world where lives and minds hang in the balance.https://s.gr-assets.com/assets/nophoto/book/111x148-bcc042a9c91a29c1d680899eff700a03.pngtruehttps://www.goodreads.com/book/show/23460726-reaching-down-the-rabbit-hole[(1676, to-read), (94, currently-reading), (43, non-fiction), (29, science), (25, nonfiction), (18, psychology), (14, medicine), (13, neuroscience), (12, medical), (9, health), (5, neurology), (4, audiobooks), (3, favorites), (3, to-buy), (3, library), (2, mental-health), (2, read-in-2016), (2, biography-memoir), (2, 2015-read), (2, books-i-own), (2, owned-but-not-read), (2, read-in-2015), (2, read-2015), (2, radio-4), (2, psych), (2, health-and-medicine), (2, psychology-brain), (2, reference), (2, memoir), (2, review-copy), (2, arc), (2, netgalley), (2, first-reads), (1, science-and-medicine), (1, 2017-books-read), (1, medi-psych), (1, psychology-and-psychotherapy), (1, ex-libris-kira), (1, to-read-nonfiction), (1, no), (1, history-of-medicine), (1, calibre-import-17), (1, want-to-read-again), (1, printed), (1, science-book-club-for-the-curious), (1, icebox), (1, educational), (1, all-things-human), (1, neuro-nerd), (1, not-to-read), (1, books-i-didn-t-finish), (1, contemporary), (1, cognition), (1, biology), (1, autobiohraphical), (1, want-to-read), (1, to-study), (1, summer-2017), (1, overdrive), (1, bought-in-2017), (1, clinical), (1, science-neuro), (1, medicine-reading-list), (1, 03-17), (1, inspirational-med-related), (1, 0overdrive), (1, professional), (1, to-read-don-t-own), (1, food-gardening), (1, books-on-kindle), (1, cognitive-science), (1, problematic-authors), (1, problematic), (1, incorrect-medicine), (1, science-non-fiction), (1, 2017-reading-challenge), (1, psychology-and-neurology), (1, dissertation-reads), (1, read-2016), (1, other), (1, own-not-read), (1, i-own), (1, northern-america), (1, true-account), (1, medicine-and-health), (1, in-my-kindle), (1, kindle), (1, bios), (1, not-young-adult), (1, oldest-tbr), (1, read-now), (1, decision-making-neuroeconomics), (1, brain-and-genes), (1, academic), (1, giveaway-winners), (1, loc-america), (1, owned), (1, one-day), (1, read-non-fiction), (1, dr-clair-goldberg)]113.0[][22351150, 17654698, 16071872, 17067162, 15815602, 17436892, 26195938, 23216795, 11410902, 21855277, 18077930, 16309770, 16059338, 18209512, 18231519, 17227579, 13341596, 15802805]4.0Reaching Down the Rabbit Hole: Extraordinary Journeys into the Human BrainReaching Down the Rabbit Hole: Extraordinary Journeys into the Human Brainhttps://www.goodreads.com/book/show/23460726-reaching-down-the-rabbit-hole27334735
4[(14708898, )]4.0027983357US"Afrikaans hoort by Nederlands: ons Afrikaanse taalverdriet" is 'n boek (en verwerkte lisensiaatverhandeling) deur Petrus van Eeden. In hierdie boek betwis Van Eeden die funksionaliteit en bestaansreg van Afrikaans as die (na sy mening rypgedrukte) standaardtaal in Suid-Afrika. Hy pleit dat Afrikaners moet herbesin en Nederlands weer as kultuurtaal moet aanvaar. Van Eeden steun taalamalgamasie.Paperbackhttps://s.gr-assets.com/assets/nophoto/book/111x148-bcc042a9c91a29c1d680899eff700a03.pngfalse1874976139afrhttps://www.goodreads.com/book/show/27983357-afrikaans-hoort-by-nederlands232[(1, afrikaans)]71995Brevitas1.0[][]1.0Afrikaans hoort by NederlandsAfrikaans hoort by Nederlandshttps://www.goodreads.com/book/show/27983357-afrikaans-hoort-by-nederlands47985533
5[(481929, )]4.209368172USIn The Mystery of the Hidden Driveway, Jennifer L. Knox expands on her inimitable cast of characters, in hilariously poignant poems. In poems like "Marriage" and "One Ton of Dirt," Knox ventures further into autobiographical territory than she's ever gone before, in ways that will startle those familiar with her previous books, exploring relationships with her exes, her parents, and her younger self. Like the best comedians (to whom she's often compared), Knox is never merely funny. Each of her speakers, even the bedraggled coyote that walks into a Quizno's, has something important to say. Bob Hicock describes the effect of her trademark dark humor perfectly when he says, "The oddities of her work create a space in which it's possible to be oddly sincere. Knox is asking what really matters, in poems that move powerfully toward an answer." www.jenniferlknox.com.Trade Paper OriginalPaperbackhttps://images.gr-assets.com/books/1291275163m/9368172.jpgfalse09826587109780982658710https://www.goodreads.com/book/show/9368172-the-mystery-of-the-hidden-driveway84[(35, to-read), (16, poetry), (1, own-paperback), (1, poetry-read), (1, american), (1, 21st-century), (1, poetry-own), (1, the-west), (1, small-press), (1, to-buy), (1, research), (1, favorite-poetry), (1, owned-not-read), (1, on-our-shelf), (1, d-melissa-broder), (1, bloof-books), (1, currently-reading), (1, literary-read), (1, literary), (1, weird-lit), (1, obscure-and-or-small-pressy), (1, funny-stuff), (1, poets)]10122010Bloof Books69.0[][]12.0The Mystery of the Hidden DrivewayThe Mystery of the Hidden Drivewayhttps://www.goodreads.com/book/show/9368172-the-mystery-of-the-hidden-driveway14251697
6[(1495617, )]3.9513227511USAfter he was stabbed and became paralyzed from the neck down, Matthew Nagle, a former high school football star, made scientific history when neurosurgeons implanted microelectrodes in his brain that recognized his thought patterns, allowing him to control a computer cursor. With the BrainGate system, Matt was able to use e-mail, manipulate a prosthetic hand, adjust TV settings, and play video games--all just by thinking about performing these tasks.\nIn The Man with the Bionic Brain and Other Victories over Paralysis, Dr. Jon Mukand, Matt's research physician and a rehabilitation specialist, weaves together his story with firsthand accounts of other courageous survivors of stroke, spinal injuries, and brain trauma and the amazing technology that has improved their lives.\nA behind-the-scenes view of cutting-edge medical research and discoveries, The Man with the Bionic Brain and Other Victories over Paralysisis an insightful and inspirational book about how biomedicine gives hope to people with disabilities and enables them to take control of their futures.Hardcoverhttps://images.gr-assets.com/books/1344705875m/13227511.jpgfalse16137405579781613740552B008B945E4https://www.goodreads.com/book/show/13227511-the-man-with-the-bionic-brain368[(29, to-read), (2, non-fiction), (1, currently-reading), (1, bookshare), (1, brain-science), (1, nf-tech), (1, nf-science), (1, nonfiction), (1, science), (1, physical-disabilities), (1, trauma), (1, biography-and-autobiography), (1, neurotexts)]172012Chicago Review Press20.0[][]5.0The Man with the Bionic Brain: And Other Victories over ParalysisThe Man with the Bionic Brain: And Other Victories over Paralysishttps://www.goodreads.com/book/show/13227511-the-man-with-the-bionic-brain18419319
7[(672891, )]3.843379686USAge has not dimmed Britain's most outrageous designer. Since she exploded on to the fashion scene more than 20 years ago, Vivienne Westwood--with her influential succession of London shops such as SEX, her famous partnership with punk impresario Malcolm McLaren, her season after season of eclectic collections--has been a controversial and sometimes bizarre figure. Born in Glossop, Derbyshire in 1941, Westwood was a schoolteacher, wife, and mother when she met McLaren in 1965. He immediately challenged what he viewed as her provincial misconceptions, and channelled her huge artistic creativity. "I was a coin and he showed me the other side", she later said. Her designs and his entrepreneurial flair ensured the duo a place in British rock and fashion history as the inspiration behind the styles of punk and New Romanticism. By 1983, when both their personal and professional partnership was over, Westwood had become a formidable fashion force in her own right, and even teetered on the edge of the Establishment when she was awarded the OBE in 1992--though she did turn up knickerless to the ceremony at Buckingham Palace. \nJane Mulvagh, a fashion historian with an insider's experience of the designer world, has written a packed and exhilarating biography of the woman who has twice been British Designer of the Year, and who continues to exasperate, scandalise, and inspire--but never to emulate. --Catherine Taylorhttps://images.gr-assets.com/books/1328602085m/3379686.jpgfalse00063868499780006386841https://www.goodreads.com/book/show/3379686-vivienne-westwood[(61, to-read), (5, fashion), (3, currently-reading), (3, biography), (1, non-fiction), (1, biographies), (1, shelfari-wishlist), (1, book-shelf), (1, shelfari-favorites), (1, memoir), (1, 0-gu), (1, on-my-bookshelf), (1, read-1999), (1, location-north-library), (1, auto-biography), (1, punk), (1, ladies), (1, cultural-history), (1, clothes), (1, anglophilia), (1, to-find), (1, fashion-biographies), (1, london-and-great-britain), (1, memoirs-and-biographies), (1, for-school), (1, biographies-diaries----), (1, fashion-designer), (1, reviewed-online), (1, biogs-music), (1, style)]33.0[][]5.0Vivienne Westwood: An Unfashionable LifeVivienne Westwood: An Unfashionable Lifehttps://www.goodreads.com/book/show/3379686-vivienne-westwood3419262
8[(304489, )]4.0018206694US"This book explores and explodes common representations and experiences of American fitness. It takes women's experiences as the center of inquiry toward an understanding of the function of fitness in our lives. This book considers a broad range of topics from an interdisciplinary perspective: generations, cultural appropriation, community development, art choreography, methodology, healing, and social justice"--Paperbackhttps://images.gr-assets.com/books/1373999220m/18206694.jpgfalse07864748079780786474806B00GDIC3NKhttps://www.goodreads.com/book/show/18206694-women-and-fitness-in-american-culture251[(3, to-read), (1, unobtained), (1, dissertation)]31102013McFarland & Company2.0[][]2.0Women and Fitness in American CultureWomen and Fitness in American Culturehttps://www.goodreads.com/book/show/18206694-women-and-fitness-in-american-culture25626044
9[(4015097, )]4.3723273757US~Best read after the original Ava Delaney series~\nThe backdrop may be grim, but Dublin city has become the centre of change. And as the humans and supernaturals figure out how to live in each other's worlds, the person who forced that change has quietly stepped aside for a peaceful life.\nAva Delaney is still trying to adjust to her own altered existence when a tainted nephal turns up on her doorstep, apparently on the run from the monster who changed Ava's life before she was even born. But she's not supposed to interfere, even for the lost souls she's vowed to help.\nBut as the first vampire leaves death in his wake, and Ava becomes an easy target to blame, she realises she has to take care of business once again. There are more secrets hidden in the shadows, more voices just waiting to be heard, and obedience has never been Ava's thing.\nOnly one thing is for certain: for people like Ava Delaney, there's no such thing as a peaceful life.ebookhttps://images.gr-assets.com/books/1420756607m/23273757.jpgtrue9781310401053https://www.goodreads.com/book/show/23273757-tainted[(172, to-read), (13, currently-reading), (3, supernatural), (3, fantasy), (2, kindle), (2, amazon), (2, ebooks), (2, paranormal-romance), (1, fiction), (1, violence-and-murder), (1, vampires), (1, urban-fantasy), (1, the-fair-folk-are-somewhere), (1, shifters), (1, monstress), (1, gods-and-goddesses), (1, angels), (1, not-at-library), (1, purchased), (1, first-things-first), (1, mount-tbr-2017), (1, maybe-read), (1, claire-farrell), (1, current-series), (1, wishlist-to-buy-ebook), (1, tbr-incomplete), (1, loved-it), (1, love), (1, 2015-reads), (1, favorites), (1, later), (1, scribd), (1, will-read-next-in-series), (1, read1), (1, series-1st), (1, owned), (1, owned-books), (1, fantasy-paranormal), (1, f), (1, my-books), (1, favourites), (1, teen-fiction-older), (1, magic-users), (1, gothic-paranormal), (1, fey), (1, distopia), (1, books-i-want), (1, to-read-not-owned), (1, t-b-r), (1, library), (1, loved), (1, to-read-own), (1, ya), (1, series), (1, nook-books-i-own), (1, n-2), (1, dark), (1, paranormal-fantasy), (1, own-ebooks), (1, farrell-claire), (1, supernatural-stories), (1, ava-delaney), (1, need-to-download), (1, waiting-to-be-published-to-read), (1, series-to-finish), (1, paranormal-to-read)]10102014Claire Farrell83.0[718908, 855715][20748857, 22521348, 20871435, 18274495, 25523134, 19506335, 18177342, 400705, 22029188, 12491164, 23631046, 16163819, 19540813, 15726288, 20707866, 25454315]7.0Tainted (Ava Delaney: Lost Souls #1)Tainted (Ava Delaney: Lost Souls #1)https://www.goodreads.com/book/show/23273757-tainted42813321
asinauthorsaverage_ratingbook_idcountry_codedescriptionedition_informationformatimage_urlis_ebookisbnisbn13kindle_asinlanguage_codelinknum_pagespopular_shelvespublication_daypublication_monthpublication_yearpublisherratings_countseriessimilar_bookstext_reviews_counttitletitle_without_seriesurlwork_id
2348[(191456, )]4.16775973USHunter and Morgan join together with a surprising new ally to fight for the people they love. In this struggle of good versus evil, who will survive to tell the tale?Paperbackhttps://s.gr-assets.com/assets/nophoto/book/111x148-bcc042a9c91a29c1d680899eff700a03.pngfalse01423011089780142301104B001LO0TU0en-UShttps://www.goodreads.com/book/show/775973.Eclipse187[(3121, to-read), (212, young-adult), (140, fantasy), (107, witches), (90, ya), (70, paranormal), (64, magic), (60, books-i-own), (57, series), (53, favorites), (51, cate-tiernan), (47, owned), (43, sweep), (40, romance), (37, fiction), (35, wicca), (34, supernatural), (33, urban-fantasy), (25, currently-reading), (20, sweep-series), (19, paranormal-romance), (18, teen), (16, witchcraft), (13, default), (13, witch), (12, my-books), (12, owned-books), (12, ebook), (11, ya-paranormal), (10, ya-fantasy), (10, childhood), (8, re-read), (8, own-it), (8, library), (8, paperback), (8, to-buy), (8, wish-list), (8, ya-books), (7, young-adult-fiction), (7, read-in-2012), (7, have), (7, favorite), (6, my-library), (6, i-own), (6, read-in-2011), (6, 21st-century), (6, young), (6, teen-fiction), (6, high-school), (5, home-library), (5, novels), (5, completed-series), (5, wicca-series), (5, 5-star), (5, e-book), (5, magick), (5, read-in-2010), (5, witch-books), (5, witchy), (4, shelfari-favorites), (4, read-in-2015), (4, read-in-2014), (4, fantasy-sci-fi), (4, female-protagonist), (4, magical), (4, kindle), (4, friendship), (4, favourites), (4, fantasy-paranormal), (4, ebooks), (4, ya-fiction), (4, adult), (4, school), (4, on-my-shelf), (4, tiernan-cate), (4, finished-series), (4, witches-magic), (4, author-tiernan-cate), (4, read-2009), (4, teen-books), (4, religion), (3, read-in-2016), (3, bookshelf), (3, female-authors), (3, on-kindle), (3, scanned), (3, own-read), (3, books), (3, rereads), (3, dutch), (3, read-in-dutch), (3, 3-stars), (3, wiccan), (3, family), (3, tbr), (3, books-i-have), (3, mystery), (3, childhood-reads), (3, book-series), (3, fantasy-series)]1062002Puffin5972.0[161320][424063, 330843, 814487, 920217]86.0Eclipse (Sweep, #12)Eclipse (Sweep, #12)https://www.goodreads.com/book/show/775973.Eclipse2224651
2349[(17623, )]3.2813384476USnbdh@ lnshr:\nhdh lHb lmZlm l'bdy, ldhy ytdfq knhr zkhr l~ l'bd fy dkhlh. ah fltHfZ `lyh mn lnqT`. knt hdy'@ tmman fy '`mqh. kn fy mqdwrh 'n tjls bmnth~ lhdw, wtsh`r blnhr whw ytHwl bbT w'nq@ l~ lyl. wlm tkn tryd shyy'an wlm ykn ynqSh shy. dhkryny dy'man. nny 'trk rwHy byn ydyk wfy rHmk. lys fy mqdwr shy 'n yfSln 'bdan, l dh khd` kl mn lakhr. dh kn ytHtm `lyk 'n tmnHy nfsk lzwjk, fmnHyh, w'Ty`yh. dh knt Sdq@ m`y fln yw'dhyn nh krym, fkwny krym@ m`h. wl tkfy `n lymn by. l'nny Ht~ fy ljnb lakhr mn lmwt s'kwn fy ntZrk. wstkwnyn l~ jnby. ln tfrqyny 'bdan fy lHy@ lakhr@. ldh l tkhfy fy lHy@. l tkhfy. dh kn ytHtm `lyk 'n tdhrfy dmw`an fdhrfyh. w`lmy fy '`mq '`mqk 'nny saty mr@ 'khr~, w'nny sakhdhk l~ l'bd.https://s.gr-assets.com/assets/nophoto/book/111x148-bcc042a9c91a29c1d680899eff700a03.pngfalsearahttps://www.goodreads.com/book/show/13384476168[(112, to-read), (5, fiction), (4, classics), (3, currently-reading), (2, novella), (2, english-literature), (2, classic), (2, british-lit), (1, classics-british), (1, bedroom-2-1), (1, otra-ed), (1, interr), (1, reviewed), (1, 20th-century), (1, d-h-lawrence), (1, 1920s-literature), (1, phryne-s-and-jack-s-bookshelf), (1, kindle-books-to-loan), (1, literature-english), (1, won-t-read-again), (1, uni), (1, shorts), (1, kindle), (1, esp), (1, enbiblio), (1, classc-30), (1, biblo), (1, fiction-british), (1, read-owned), (1, books-read-in-2016), (1, my-lib), (1, historical-fiction), (1, uk), (1, existential), (1, كتب-مترجمة), (1, novels), (1, next-ebook), (1, 2014-between-the-wars), (1, penguin), (1, war-stories), (1, owned-books), (1, elte), (1, read-2013), (1, hf-world-war-i), (1, british-literature), (1, novellas), (1, mtbr-challenge-2013), (1, fiction-20th-century), (1, e-books), (1, i-own), (1, lawrence), (1, owned), (1, catalogged), (1, step-back-in-time), (1, sentimental-journey), (1, zz-animal-kingdom), (1, quick-read), (1, cozy-cup-of-tea), (1, z-20th-century-20s), (1, short-stories), (1, literature-modern), (1, library), (1, european-authors), (1, english-authors), (1, compilation-only), (1, fiction-lit), (1, 2010-read), (1, d-h--lawrence), (1, english-language-modernism)]182004dr lHwr11.0[][]3.0الخنفساء المنقطةالخنفساء المنقطةhttps://www.goodreads.com/book/show/133844761921205
2350[(10937, )]3.4315795314USHow should money be distributed? What is the future of food? How do we identify and combat stereotyping? Emerging engages students with meaningful contemporary issues so that they can develop the skills they need to address the large questions that will shape their lives. To help students learn to bridge public and academic conversations, Emergingfocuses its support on building key academic skills: reading critically, synthesizing, arguing, using evidence, and revising. With a more accessible range of readings, the second edition includes substantial and shorter selections, as well as visuals and online multimodal texts that will challenge students' assumptions and spark considered writing. The print text is now integrated with e-Pages for Emerging,designed to take advantage of what the Web can do.Paperbackhttps://images.gr-assets.com/books/1345686225m/15795314.jpgfalse14576019749781457601972https://www.goodreads.com/book/show/15795314-emerging640[(67, to-read), (5, currently-reading), (1, school-reads), (1, gramatik), (1, required-reading), (1, professional-development), (1, on-writing), (1, nonfiction-miscellaneous), (1, books-i-own), (1, writing-reference), (1, teaching-reference), (1, anthologies)]412013Bedford/St. Martin's18.0[][]1.0Emerging: Contemporary Readings for WritersEmerging: Contemporary Readings for Writershttps://www.goodreads.com/book/show/15795314-emerging21517498
2351[(2448, )]4.0910706848USThe rich landowner Sir Charles Baskerville is found dead in the park of his manor surrounded by the grim moor of Dartmoor, in the county of Devon. His death seems to have been caused by a heart attack, but the victim's best friend, Dr. Mortimer, is convinced that the strike was due to a supernatural creature, which haunts the moor in the shape of an enormous hound, with blazing eyes and jaws. In order to protect Baskerville's heir, Sir Henry, who's arriving to London from Canada, Dr. Mortimer asks for Sherlock Holmes' help, telling him also of the so-called Baskervilles' curse, according to which a monstrous hound has been haunting and killing the family males for centuries, in revenge for the misdeeds of one Sir Hugo Baskerville, who lived at the time of Oliver Cromwell.https://images.gr-assets.com/books/1350337368m/10706848.jpgfalse115366318X9781153663182B00JA6NQLUhttps://www.goodreads.com/book/show/10706848-baskervillen-koira230[(4849, classics), (4073, mystery), (2227, fiction), (1403, favorites), (940, crime), (857, classic), (629, sherlock-holmes), (597, owned), (582, to-read), (535, books-i-own), (432, detective), (296, mysteries), (289, 1001-books), (251, thriller), (232, british), (225, mystery-thriller), (225, literature), (213, owned-books), (212, series), (201, novels), (194, favourites), (185, kindle), (181, historical-fiction), (174, 1001), (174, adventure), (162, sherlock), (156, english), (149, british-literature), (142, school), (139, default), (139, england), (135, horror), (130, mystery-suspense), (128, victorian), (127, classic-literature), (125, ebook), (125, adult), (125, book-club), (123, audiobook), (123, gothic), (117, audiobooks), (117, historical), (115, crime-mystery), (113, novel), (113, arthur-conan-doyle), (112, crime-fiction), (109, mystery-crime), (108, 19th-century), (108, suspense), (103, ebooks), (103, 1001-books-to-read-before-you-die), (90, audio), (87, library), (83, my-library), (81, my-books), (78, my-ebooks), (78, i-own), (77, 20th-century), (74, read-for-school), (71, books), (71, detective-fiction), (70, adult-fiction), (69, holmes), (66, 1900s), (63, re-read), (63, 1001-books-you-must-read-before-you), (62, to-buy), (62, uk), (59, english-literature), (59, read-in-english), (57, read-in-2014), (56, read-in-2016), (56, classic-fiction), (54, crime-thriller), (52, read-in-2013), (52, read-in-2012), (51, murder-mystery), (51, e-books), (50, childhood), (48, read-in-2017), (48, detectives), (48, e-book), (48, brit-lit), (47, for-school), (46, audible), (46, 4-stars), (45, detective-stories), (43, read-in-2015), (43, mistery), (42, own-it), (42, classics-to-read), (42, audio-books), (42, 1001-books-to-read), (42, short-stories), (40, sir-arthur-conan-doyle), (39, the-classics), (39, british-lit), (38, crime-and-mystery), (36, murder), (36, audio-book)]120.0[185869, 830529][77608, 215492, 192887, 184594, 428537, 141270, 188214, 278854, 498490]5.0Baskervillen Koira (Sherlock Holmes #5)Baskervillen Koira (Sherlock Holmes #5)https://www.goodreads.com/book/show/10706848-baskervillen-koira3311984
2352[(4774780, )]4.1414058565UShdh lktb y`tbr mjmw`@ mn ftwy l`lm, Hyth tm khtSr lftw~ fyh dwn 'n yHyl `n lmqSwd mn lftw~, whw l ykhtS blmr'@ nm bl'sy'l@ lty ts'l `nh lmr'@.https://images.gr-assets.com/books/1337382303m/14058565.jpgfalsearahttps://www.goodreads.com/book/show/14058565202[(20, to-read), (1, to-re-read), (1, 2017-book-room), (1, owned-books), (1, ورقي), (1, ديني), (1, إسلاميات), (1, mybooks), (1, العلوم-الشرعية), (1, cat-b-women)]4.0[][]1.0أكثر من ألف دعوة في اليوم والليلةأكثر من ألف دعوة في اليوم والليلةhttps://www.goodreads.com/book/show/1405856519207675
2353[(4677434, )]4.4523380872USHarga: Rp47.000\nGenre: Nonfiksi Remaja Islami\nPacaran bagi kebanyakan remaja mungkin mengasyikkan. Tapi tahukah kamu? Islam itu tidak mengenal pacaran, Bro/Sist. Karena pacaran merupakan perbuatan yang mendekati zina. Lebih banyak mudharat daripada manfaatnya.\nKamu mungkin menganggap, pacarmu adalah segalanya. Berpikir, kalau si doi udah pasti akan menjadi pendampingmu kelak. Sampai-sampai memanggilnya pun udah Mama-Papa, bahkan nggak sedikit yang udah berani ngelakuin hubungan intim layaknya suami-istri. Astagfirullahal adzim. Apa kamu nganggep ini hal biasa, Bro/Sist? Hadeuh... hadeuh.... *Nepok jidat*\nIngat dong Bro/Sist, PACARMU ITU BELUM TENTU JODOHMU! Jangan sampai deh nyerahin segalanya. Yang udah pasti paling banyak ruginya itu di pihak cewek, lho, Sist! Begitu cowokmu udah bosan, kamu ditinggalin begitu aja, dalam keadaan hamil pula. Ibaratnya, habis manis sepah dibuang. Kalau udah kayak gini, siapa coba yang bakal ikut nanggung aib? Orangtua kamu juga, 'kan? Emangnya kamu nggak kasihan sama orangtuamu?? Jadi.... udah deh nggak usah pacaran, Bro/Sist. Lebih banyak sia-sianya. Tapi kalau kamu udah terlanjur pacaran, ya udah putusin aja sekarang!\nBuku ini memotret kondisi nyata pergaulan para remaja saat ini. Penulis menyusun buku ini berdasarkan pengalamannya dalam membimbing dan menerima konsultasi dari para remaja seputar pacaran. Melalui buku ini, penulis ingin berbagi kiat kepada para remaja agar tidak galau soal pacaran dan memberi solusi tentang indahnya menikah tanpa pacaran.\nTersedia di toko buku nasional se-Indonesia.\nPembelian onlie:\nRepublik Fiksi\n@republikfiksi\nPesan buku via sms / whatsapp / line di no 087885575247, 081283144174, 08571176399, 089639278507Paperbackhttps://images.gr-assets.com/books/1413441206m/23380872.jpgfalse97979587799789797958770indhttps://www.goodreads.com/book/show/23380872-pacarmu-belum-tentu-jodohmu216[(23, to-read), (3, currently-reading), (1, non-fiksi), (1, islam)]72014Penerbit Wahyu Qolbu11.0[][]1.0Pacarmu Belum Tentu JodohmuPacarmu Belum Tentu Jodohmuhttps://www.goodreads.com/book/show/23380872-pacarmu-belum-tentu-jodohmu42939899
2354[(13663, ), (121656, illustrator)]4.0031868148USOpowiesc o Despero to zadziwiajaca, trzymajaca w napieciu basn, laczaca elementy opowiesci przygodowej, fantastyki i horroru. Glownym bohaterem jest Despero, mala myszka z wielkimi uszami, ktora wraz z rodzina mieszka we wspanialym zamku. Jest niezwykla myszka, uwielbia muzyke, czyta ksiazki, zakochuje sie w ksiezniczce. Zarowno te cechy, jak i wyglad tak rozniace ja od innych myszy, sprawiaja, ze Despero jest odrzucony przez najblizsza rodzine i otoczeniehttps://images.gr-assets.com/books/1482670865m/31868148.jpgfalse9788372362438polhttps://www.goodreads.com/book/show/31868148-dzielny-despero294[(30728, to-read), (1934, fantasy), (1266, favorites), (1148, currently-reading), (926, childrens), (871, fiction), (708, children), (564, children-s), (504, young-adult), (475, children-s-books), (466, newbery), (440, books-i-own), (421, middle-grade), (382, animals), (347, owned), (344, kids), (330, adventure), (256, childrens-books), (227, childhood), (201, juvenile), (192, classics), (181, children-s-lit), (180, ya), (180, kids-books), (179, children-s-literature), (154, juvenile-fiction), (123, read-aloud), (122, newbery-medal), (106, owned-books), (105, chapter-books), (103, audiobook), (101, newbery-winners), (99, newbery-award), (99, newberry), (97, childrens-lit), (94, audio), (91, childrens-literature), (91, fairy-tale), (90, library), (88, fairy-tales), (83, school), (82, youth), (79, childhood-books), (74, default), (74, childhood-favorites), (74, audiobooks), (74, children-s-fiction), (73, read-alouds), (70, novels), (68, award-winners), (63, middle-school), (62, award-winner), (62, kid-lit), (61, my-books), (56, i-own), (56, kate-dicamillo), (56, my-library), (56, childrens-fiction), (55, mice), (54, elementary), (52, fantasy-sci-fi), (51, children-books), (50, read-for-school), (50, kid-books), (48, favourites), (48, all-time-favorites), (47, book-club), (46, newbery-winner), (45, friendship), (45, classroom-library), (45, newbery-medal-winners), (45, animal-fiction), (44, audio-books), (44, classic), (44, childhood-reads), (44, animal), (42, favorite-books), (42, own-it), (40, re-read), (39, kindle), (39, newbery-books), (39, 4th-grade), (38, books), (38, animal-stories), (37, shelfari-favorites), (37, newbery-award-winners), (37, young-readers), (36, school-books), (36, classroom), (35, movie), (34, 5th-grade), (34, children-young-adult), (34, ya-fiction), (33, libs-642), (33, favorite), (33, borrowed), (32, children-s-chapter-books), (32, newberry-winners), (32, children-ya), (32, junior-fiction)]Philip Wilson4.0[][607931, 24300, 24686, 62151, 39980, 2768169, 530582, 43475, 403722, 1116594, 785453, 854764, 984168, 207330, 1838166, 41457, 822392, 6729699]1.0Dzielny DesperoDzielny Desperohttps://www.goodreads.com/book/show/31868148-dzielny-despero1508178
2355[(868034, )]3.113901589USThrough gentle, poetic text and outstanding watercolor paintings, children will discover that special friend each one of us has--our shadow--who keeps our dreams "secret and safe". Full-color illustrations.Hardcoverhttps://images.gr-assets.com/books/1256081986m/3901589.jpgfalse06895043229780689504327https://www.goodreads.com/book/show/3901589-i-have-a-friend32[(8, picture-books), (7, to-read), (2, shadows), (1, picture-books-2017), (1, social-justice-diversity), (1, jane), (1, outdoor-learning), (1, weeding-gems), (1, picture-books-storytime), (1, picture-books-lap-reads), (1, fiction), (1, childrens), (1, 3-4-september), (1, books-in-the-church-library), (1, juliet), (1, light), (1, friendship), (1, back-to-school), (1, motheread-books), (1, favourite-children-s-books), (1, sarah-natalie-books), (1, multicultural), (1, kids), (1, from-the-library), (1, sebastian-s-books), (1, books-we-own), (1, science-literature), (1, read-alouds), (1, light-dark), (1, ece-3601), (1, picture-book)]191987Margaret K. McElderry Books17.0[][]3.0I Have a Friend: Keiko NarahashiI Have a Friend: Keiko Narahashihttps://www.goodreads.com/book/show/3901589-i-have-a-friend3946909
2356[(10908470, ), (10907453, Translator)]4.5023923991US'Tiny Owl books are beautiful and deserve to find an audience in this country. It's wonderful that we are being introduced to such fine writers and artists.' David Almond\nOne day a large egg is left in a forest. It hatches out a chick who needs care and love. But his mother isn't there! So a wonderfully unlikely assortment of foster parents takes over the job of trying to bring that chick up...Hardcoverhttps://images.gr-assets.com/books/1418836542m/23923991.jpgfalse19103280229781910328026enghttps://www.goodreads.com/book/show/23923991-a-bird-like-himself29[(2, to-read), (1, 1000-books-before-kindergarten), (1, picture-books)]2015Tiny Owl Publishing Ltd4.0[][]1.0A Bird Like HimselfA Bird Like Himselfhttps://www.goodreads.com/book/show/23923991-a-bird-like-himself43530110
2357B01BU5HT0C[(14856672, )]3.6029151418USBad boys are only good for one thing.\nWhat would Granddad think?\nRugged charm can only get playboy cop Sebastian McCoyso far. He wants to settle down and find a meaningful connection--but his family might not be ready to deal with the fallout. Will his intense love and loyalty to the job doom him from committing to his one true love?\nThere's too much at stake.\nPolice dispatcher Cody Hartis a lifeline for police officers--including the sexy and infuriating Sebastian. He loves his high-stress job but often sees the worst of humanity. He needs a loyal man to enjoy the bright side of life with him, but he's been burned before.\nI can't keep him off my mind.\nWhether they like it or not, Sebastian and Cody rely on each otherevery day on the job to keep themselves and others safe. When they become a team at work and at home, sparks are kindled into a secret workplace affair. Sebastian can't let his police family down, while Cody can't let in a guy who will turn his affections into gossip. Can they both overcome their own fearsto hold onto each other for good?\nKeyed Inis a gay romance novel. It's the second novel in the "Costal Charm" series but can stand alone. It has a happily ever after ending with no cliffhanger.https://s.gr-assets.com/assets/nophoto/book/111x148-bcc042a9c91a29c1d680899eff700a03.pngtrueB01BU5HT0Cen-UShttps://www.goodreads.com/book/show/29151418-keyed-in222[(62, to-read), (17, currently-reading), (13, m-m), (7, ku), (7, series), (6, romance), (4, law-enforcement), (4, m-m-romance), (4, mm-romance), (4, kindle-unlimited), (3, gay), (3, mm), (2, contemporary), (2, m-m-contemporary), (2, unlimited), (2, family-drama), (2, relationship), (2, age-gap), (1, spank-me), (1, cop-military-bodyguard-pi), (1, mm-love), (1, detective-police), (1, added-2017), (1, coastal-charm-series), (1, ashwood), (1, glbt), (1, own-not-read), (1, maybe), (1, last-year), (1, books-to-consider), (1, cops), (1, cops-detectives-sheriff), (1, 2-stars), (1, tbr), (1, m-m-books-i-own), (1, to-read-owned-mm), (1, lendable), (1, series-or-anthology), (1, dnf), (1, blah), (1, boys-on-boys), (1, maine), (1, half-stars), (1, erotica), (1, calibre), (1, i-like-this-author), (1, short-stories), (1, m-m-bdsm), (1, lovely-books), (1, love-at-first-sight), (1, hot-hot-hot), (1, hot-couple), (1, hot-cops), (1, gay-for-you), (1, beauty-boy), (1, alpha-male), (1, agent-cop), (1, cute-series), (1, kindle-un), (1, adult-romance), (1, 2-povs), (1, men-in-uniform), (1, part-of-a-series), (1, e-books), (1, books-read-in-2016), (1, 2016-reading-challenge), (1, mmromance), (1, cop-firefighter-emt), (1, mm-coworkers), (1, mm-cop-fire-feds-pi-etc), (1, 01-03-16), (1, workplace-romance), (1, uniforms), (1, slow-burn), (1, short-reads), (1, ku-read), (1, cute-dude-with-macho-dude), (1, all-the-fluffy-feels), (1, own-amazon), (1, free-ku), (1, erotic-romance), (1, borrowed), (1, in-dropbox), (1, own-not-lendable), (1, lgbt-ménage), (1, lending-sadly-not-enabled), (1, cops-fbi), (1, 11-1-2015), (1, gay-romance), (1, author-s-series-must-buy), (1, series-sequels), (1, own-copy), (1, glbtq), (1, besties), (1, aaa-2), (1, prime-read), (1, opposites), (1, law-enf), (1, kink), (1, interested)]220.0[884776][18401815, 29911727, 26209145, 28117696, 29490618, 28241883, 25783348, 29214301, 25395515, 28795188, 25308083]18.0Keyed In (Coastal Charm Book 2)Keyed In (Coastal Charm Book 2)https://www.goodreads.com/book/show/29151418-keyed-in49310720